标记图像,并且计算图像的面积等
【数字图像处理】图像的面积与周长计算
【数字图像处理】图像的⾯积与周长计算⼆值化图像区域标记在⼆值化图像中，相互联结的⿊像素集合成为⼀个（⿊）区域，通过对图像内每个区域进⾏标记操作，求得区域的数⽬。
处理前的f是⼆值的，像素要么为0（⿊），要么为255（⽩）处理后每个像素的值即为其所处理区域的标号（1，2，3，。
）标记规则1.初始化标记为0，从左到右，从上到下逐个像素扫描2.若该点为物体颜⾊，则继续判断该点的左上、正上，右上及左前点是否都不为物体，则标号加1，若该点为背景⾊，则跳过。
3.优先级依次为右上点，正上点，左上点及左前点。
右上点的优先级最⾼，左前点的优先级最低。
4.继续遍历图像，若右上点为物体，则该点标记上与右上点相同的值。
5.若右上不为物体，则判断正上点，左上点及左前点特殊情况：当前点的右上点及左前点为不同标记，正上点和左上点不为物体，则当前点标记同右上点置相同的值，把所有标记与左前点相同的像素值都标记成与右上点同样的值。
如图下⾯的⿊点，如果出现上⾯的特殊情况，可以这样处理：int sign_count = 0;int sum[5] = {0};int sign_temp;for(int y = 1; y<120 - 1;y++)for(int x = 1; x<180 - 1;x++){//只有当像素点为物体，才进⾏下⾯的判断。
if(img[y][x] == 0){//解决特殊情况if(img[y-1][x+1] != img [y][x-1] && img[y-1][x-1] == img[y-1][x]){img[y][x] = img[y - 1][x + 1];sign_temp = img [y][x-1];for(int i = 0; i<y; i ++)for(int j = 0; j<x;j++){if(img[i][j] == sign_temp)img[i][j] = img[y][x]}}//如果该点周围四个点皆为背景，则说明该点新的物体，将标记累加，并将该点赋值为标记。
inpaint_telea算法原理
inpaint_telea算法原理Inpainting是一种图像修复技术，它可以从图像中移除不想要的内容，并用合适的图像信息填补这些区域。
其中，inpaint_telea算法是一种经典的基于偏微分方程的inpainting算法。
本文将详细介绍inpaint_telea算法的原理。
inpaint_telea算法是由Alexandre Telea在2004年提出的。
这个算法的核心思想是利用图像区域中的局部信息来重建缺失区域的像素值。
具体来说，它假设缺失区域的像素值可以由其周围已知像素值通过其中一种方式计算得到。
1.初始化：将输入图像拷贝到输出图像中，同时创建一个标记图像，用于标记待修复的像素区域。
2.检测缺失像素：遍历输入图像，将缺失像素的位置标记在标记图像中。
对于RGB图像，可以通过检测像素值是否为0来判断是否缺失。
3.寻找边界像素：在标记图像上进行遍历，找到位于缺失区域与非缺失区域之间的边界像素。
4. 修复像素：对于每个边界像素，计算它的修复值。
inpaint_telea 算法采用了基于偏微分方程的方法来计算修复值。
具体来说，它使用了Poisson方程，该方程可以在已知边界值的情况下，通过最小化梯度的平方和来计算未知像素值。
修复值的计算涉及到求解一个线性方程组，可以通过迭代的方法进行求解。
5.更新标记图像：将修复像素对应的标记图像中的像素值更新为1，表示这些像素已经修复。
6.迭代修复过程：重复进行步骤4和步骤5，直到所有的边界像素都被修复或达到设定的迭代次数。
每次迭代都会增加像素的修复范围，使算法能够利用新修复的像素来计算更多像素的修复值。
7.输出结果：将修复结果输出为最终图像。
inpaint_telea算法的优点是能够产生具有平滑边界的修复结果，并且在边界区域上具有较好的局部一致性。
它在处理小面积缺失以及文本、纹理等复杂结构时表现良好。
然而，该算法在处理大面积缺失以及存在大量细节的图像时，可能会出现一些模糊或失真的问题。
blob目标面积
blob目标面积
blob目标面积是指一个blob（一种类似于斑点或斑块的图像区域）的表面积。
它是一个用于描述图像中目标大小的重要指标。
在计算机视觉和图像处理领域，blob目标面积被广泛应用于图像分割、目标检测和跟踪等任务中。
为了计算blob目标面积，我们可以使用多种方法。
其中一种常用的方法是使用像素计数法。
首先，我们将图像转换为二值图像，即将图像中的目标区域设为白色，背景区域设为黑色。
然后，通过计算白色像素的数量，即可得到blob目标的面积。
另一种方法是通过计算blob的轮廓，然后根据轮廓的形状计算面积。
在实际应用中，blob目标面积通常与其他特征一起使用，以辅助目标检测和分类任务。
例如，在医学图像处理中，医生可以通过测量肿瘤的面积来评估病情的严重程度。
在工业自动化中，blob目标面积可以用于检测产品缺陷或计算材料的使用量。
除了计算blob目标面积，还可以使用其他方法来描述目标的大小。
例如，可以使用目标的最大尺寸、最小尺寸或平均尺寸等指标。
这些指标可以提供关于目标的不同方面的信息，从而帮助我们更好地理解和分析图像中的目标。
blob目标面积是一种用于描述图像中目标大小的重要指标。
通过计算图像中blob目标的面积，我们可以获得有关目标的重要信息，从
而帮助我们在计算机视觉和图像处理任务中取得更好的结果。
图像区域求质心，面积
图像区域求质⼼，⾯积⼆值图像中⼤于0的像素个数就是图像的⾯积坐标x乘以每个像素点的值求和，除以图像中像素值的和得到质⼼注意图像的宽⾼范围从1-width，1-height。
/jia20003/article/details/17596645图像处理之计算⼆值连通区域的质⼼⼀：⼏何距(Geometric Moments)知识与质⼼寻找原理1. Image Moments是图像处理中⾮常有⽤的算法，可以⽤来计算区域图像的质⼼，⽅向等⼏何特性，同时Mpq的⾼阶具有旋转不变性，可以⽤来实现图像⽐较分类，正是因为Moments有这些特性，很多⼿绘油画效果也会基于该算法来模拟实现。
它的数学表达为：它的低阶M00，M01, M10可以⽤来计算质⼼，中⼼化以后M11,M02,M20可以⽤来计算区域的⽅向/⾓度2. 什么是质⼼就是通过该点，区域达到⼀种质量上的平衡状态，可能物理学上讲的⽐较多，简单点的说就是规则⼏何物体的中⼼，不规则的可以通过挂绳⼦的⽅法来寻找。
⼆：算法流程1. 输⼊图像转换为⼆值图像2. 通过连通组件标记算法找到所有的连通区域，并分别标记3. 对每个连通区域运⽤计算⼏何距算法得到质⼼4. ⽤不同颜⾊绘制连通区域与质⼼，输出处理后图像三：算法效果左边为原图，右边蓝⾊为连通组件标记算法处理以后结果，⽩⾊点为质⼼四：关键代码解析1. 计算⼏何距算法代码double m00 = moments(pixels, width, height, 0, 0);double xCr = moments(pixels, width, height, 1, 0) / m00;// rowdouble yCr = moments(pixels, width, height, 0, 1) / m00;// columnreturn new double[]{xCr, yCr};2. 连通组件标记算法代码参见这⾥:五：程序源代码[java]1. package com.gloomyfish.image.moments;2.3. import java.awt.image.BufferedImage;4.5. import com.gloomyfish.filter.study.AbstractBufferedImageOp;6. import com.gloomyfish.rice.analysis.FastConnectedComponentLabelAlg;7. // Geometric Moments Computing8. // low-order moments - calculate the center point9. // second-order moments - get angle size10. // projection -11. public class GeometricMomentsFilter extends AbstractBufferedImageOp {12.13. @Override14. public BufferedImage filter(BufferedImage src, BufferedImage dest) {15. int width = src.getWidth();16. int height = src.getHeight();17.18. if ( dest == null )19. dest = createCompatibleDestImage( src, null );20.21. // first step - make it as binary image output pixel22. int[] inPixels = new int[width*height];23. int[] outPixels = new int[width*height];24. getRGB( src, 0, 0, width, height, inPixels );25. int index = 0;26. for(int row=0; row<height; row++) {27. int tr = 0;28. for(int col=0; col<width; col++) {29. index = row * width + col;30. tr = (inPixels[index] >> 16) & 0xff;31. if(tr > 127)32. {33. outPixels[index] = 1;34. }35. else36. {37. outPixels[index] = 0;38. }39. }40. }41.42. // second step, connected component labeling algorithm43. FastConnectedComponentLabelAlg ccLabelAlg = new FastConnectedComponentLabelAlg();44. ccLabelAlg.setBgColor(0);45. int[] labels = ccLabelAlg.doLabel(outPixels, width, height);46. int max = 0;47. for(int i=0; i<labels.length; i++)48. {49. if(max < labels[i])50. {51. System.out.println("Label Index = " + labels[i]);52. max = labels[i];53. }54. }55.56. // third step, calculate center point of each region area(connected component)57. int[] input = new int[labels.length];58. GeometricMomentsAlg momentsAlg = new GeometricMomentsAlg();59. momentsAlg.setBACKGROUND(0);60. double[][] labelCenterPos = new double[max][2];61. for(int i=1; i<=max; i++)62. {63. for(int p=0; p<input.length; p++)64. {65. if(labels[p] == i)66. {67. input[p] = labels[p];68. }69. else70. {71. input[p] = 0;72. }73. }74. labelCenterPos[i-1] = momentsAlg.getGeometricCenterCoordinate(input, width, height);75. }76.77. // render the each connected component center position78. for(int row=0; row<height; row++) {79. for(int col=0; col<width; col++) {80. index = row * width + col;81. if(labels[index] == 0)82. {83. outPixels[index] = (255 << 24) | (0 << 16) | (0 << 8) | 0; // make it as black for background84. }85. else86. {87. outPixels[index] = (255 << 24) | (0 << 16) | (0 << 8) | 100; // make it as blue for each region area88. }89. }90. }91.92. // make it as white color for each center position93. for(int i=0; i<max; i++)94. {95. int crow = (int)labelCenterPos[i][0];96. int ccol = (int)labelCenterPos[i][1];97. index = crow * width + ccol;98. outPixels[index] = (255 << 24) | (255 << 16) | (255 << 8) | 255;99. }100.101. setRGB( dest, 0, 0, width, height, outPixels );102. return dest;103. }104.105. }package com.gloomyfish.image.moments;import java.awt.image.BufferedImage;import com.gloomyfish.filter.study.AbstractBufferedImageOp;import com.gloomyfish.rice.analysis.FastConnectedComponentLabelAlg;// Geometric Moments Computing// low-order moments - calculate the center point// second-order moments - get angle size// projection -public class GeometricMomentsFilter extends AbstractBufferedImageOp {@Overridepublic BufferedImage filter(BufferedImage src, BufferedImage dest) {int width = src.getWidth();int height = src.getHeight();if ( dest == null )dest = createCompatibleDestImage( src, null );// first step - make it as binary image output pixelint[] inPixels = new int[width*height];int[] outPixels = new int[width*height];getRGB( src, 0, 0, width, height, inPixels );int index = 0;for(int row=0; row<height; row++) {int tr = 0;for(int col=0; col<width; col++) {index = row * width + col;tr = (inPixels[index] >> 16) & 0xff;if(tr > 127){outPixels[index] = 1;}else{outPixels[index] = 0;}}}// second step, connected component labeling algorithmFastConnectedComponentLabelAlg ccLabelAlg = new FastConnectedComponentLabelAlg();ccLabelAlg.setBgColor(0);int[] labels = ccLabelAlg.doLabel(outPixels, width, height);int max = 0;for(int i=0; i<labels.length; i++){if(max < labels[i]){System.out.println("Label Index = " + labels[i]);max = labels[i];}}// third step, calculate center point of each region area(connected component)int[] input = new int[labels.length];GeometricMomentsAlg momentsAlg = new GeometricMomentsAlg();momentsAlg.setBACKGROUND(0);double[][] labelCenterPos = new double[max][2];for(int i=1; i<=max; i++){for(int p=0; p<input.length; p++){if(labels[p] == i){input[p] = labels[p];}else{input[p] = 0;}}labelCenterPos[i-1] = momentsAlg.getGeometricCenterCoordinate(input, width, height);}// render the each connected component center positionfor(int row=0; row<height; row++) {for(int col=0; col<width; col++) {index = row * width + col;if(labels[index] == 0){outPixels[index] = (255 << 24) | (0 << 16) | (0 << 8) | 0; // make it as black for background}else{outPixels[index] = (255 << 24) | (0 << 16) | (0 << 8) | 100; // make it as blue for each region area }}}// make it as white color for each center positionfor(int i=0; i<max; i++){int crow = (int)labelCenterPos[i][0];int ccol = (int)labelCenterPos[i][1];index = crow * width + ccol;outPixels[index] = (255 << 24) | (255 << 16) | (255 << 8) | 255;}setRGB( dest, 0, 0, width, height, outPixels );return dest;}}Moment算法代码：[java]1. package com.gloomyfish.image.moments;2.3. public class GeometricMomentsAlg {4. private int BACKGROUND = 0; // background color5. private int labelIndex = 1;6.7. public GeometricMomentsAlg()9. System.out.println("Geometric Moments Algorithm Initialziation...");10. }11.12. public int getLabelIndex() {13. return labelIndex;14. }15.16. public void setLabelIndex(int labelIndex) {17. belIndex = labelIndex;18. }19.20. public int getBACKGROUND() {21. return BACKGROUND;22. }23.24. public void setBACKGROUND(int bACKGROUND) {25. BACKGROUND = bACKGROUND;26. }27.28. public double[] getGeometricCenterCoordinate(int[] pixels, int width, int height)29. {30. double m00 = moments(pixels, width, height, 0, 0);31. double xCr = moments(pixels, width, height, 1, 0) / m00; // row32. double yCr = moments(pixels, width, height, 0, 1) / m00; // column33. return new double[]{xCr, yCr};34. }35.36. public double moments(int[] pixels, int width, int height, int p, int q)37. {38. double mpq = 0.0;39. int index = 0;40. for(int row=0; row<height; row++)41. {42. for(int col=0; col<width; col++)43. {44. index = row * width + col;45. if(pixels[index] == BACKGROUND) continue;46. mpq += Math.pow(row, p) * Math.pow(col, q);47. }48. }49. return mpq;50. }51.52. public double centralMoments(int[] pixel, int width, int height, int p, int q)53. {54. double m00 = moments(pixel, width, height, 0, 0);55. double xCr = moments(pixel, width, height, 1, 0) / m00;56. double yCr = moments(pixel, width, height, 0, 1) / m00;57. double cMpq = 0.0;58. int index = 0;59. for(int row=0; row<height; row++)60. {61. for(int col=0; col<width; col++)62. {63. index = row * width + col;64. if(pixel[index] == BACKGROUND) continue;65. cMpq += Math.pow(row - xCr, p) * Math.pow(col - yCr, q);66. }67. }68. return cMpq;69. }70.71. public double normalCentralMoments(int[] pixel, int width, int height, int p, int q)72. {73. double m00 = moments(pixel, width, height, 0, 0);74. double normal = Math.pow(m00, ((double)(p+q+2))/2.0d);75. return centralMoments(pixel, width, height, p, q)/normal;77. }。
车牌识别系统的设计--课程设计报告
目录一、摘要: (3)二、设计目的和意义: (3)2.1、设计目的： (3)2.2、设计意义： (2)三、设计原理: (2)四、详细设计步骤: (2)4.1、提出总体设计方案: (3)4.2、各模块的实现: (4)五、设计结果及分析 (20)六、总结: (21)七、体会 (22)八、参考文献: (22)一、摘要:随这图形图像技术的发展，现在的车牌识别技术准确率越来越高，识别速度越来越快。
无论何种形式的车牌识别系统，它们都是由触发、图像采集、图像识别模块、辅助光源和通信模块组成的。
车牌识别系统涉及光学、电器、电子控制、数字图像处理、计算视觉、人工智能等多项技术。
触发模块负责在车辆到达合适位置时，给出触发信号，控制抓拍。
辅助光源提供辅助照明，保证系统在不同的光照条件下都能拍摄到高质量的图像。
图像预处理程序对抓拍的图像进行处理，去除噪声，并进行参数调整。
然后通过车牌定位、字符识别，最后将识别结果输出。
二、设计目的和意义:2.1、设计目的：1、巩固理论课上所学的知识，理论联系实践。
2、锻炼学生的动手能力，激发学生的研究潜能，提高学生的协作精神。
3、通过本次二级项目的设计，能够综合运用所学理论知识，拓宽知识面，系统地进行电子电路的工程实践训练，培养工程师的基本技能，提高分析问题和解决问题的能力。
2.2、设计意义：车辆牌照在交通系统管理中有着重要的作用，通过它可以检索车辆的各项重要信息，实现车辆的控制、运输安排、停车管理、自动收费、事故处理等功能，从而给交通系统的自动管理提供极大的方便。
车牌定位系统的目的在于正确获取整个图像中车牌的区域，并识别出车牌号。
通过设计实现车牌识别系统，能够提高学生分析问题和解决问题的能力，还能培养一定的科研能力。
三、设计原理:牌照自动识别是一项利用车辆的动态视频或静态图像进行牌照号码、牌照颜色自动识别的模式识别技术。
其硬件基础一般包括触发设备、摄像设备、照明设备、图像采集设备、识别车牌号码的处理机等，其软件核心包括车牌定位算法、车牌字符分割算法和光学字符识别算法等。
数学图形的重点标记
数学图形的重点标记一、平面几何图形的重点标记1.1 点：直线的交点、圆心、角的顶点等。
1.2 直线：垂直、平行、斜线、对称轴等。
1.3 圆：圆心、半径、直径、弧、扇形等。
1.4 三角形：顶点、底边、高、中线、角平分线等。
1.5 四边形：对边、对角、邻边、对角线、高、中线、角平分线等。
1.6 梯形：上底、下底、腰、高、中线等。
1.7 平行四边形：对边平行且相等、对角相等、邻角互补等。
1.8 矩形：对边平行且相等、对角相等、四个角都是直角等。
1.9 菱形：对边平行且相等、对角相等、四条边都相等等。
1.10 正方形：对边平行且相等、对角相等、四条边都相等、四个角都是直角等。
二、立体几何图形的重点标记2.1 点：球心、圆心、立方体顶点等。
2.2 线：球面上的纬线、经线、立方体的对角线等。
2.3 面：球面、立方体的表面、圆柱面、圆锥面等。
2.4 三棱锥：顶点、底面、高、中线等。
2.5 圆柱：底面、顶面、高、母线等。
2.6 圆锥：底面、顶点、高、母线等。
2.7 球体：球心、半径、纬线、经线等。
三、图形变换的重点标记3.1 平移：方向、距离、轨迹等。
3.2 旋转：中心点、旋转方向、旋转角度、轨迹等。
3.3 轴对称：对称轴、对称点、对称图形等。
3.4 中心对称：对称中心、对称点、对称图形等。
四、图形性质的重点标记4.1 角度：内角、外角、对顶角、邻补角、同位角、同旁内角等。
4.2 弧长：圆心角、半径、弧长等。
4.3 面积：三角形、矩形、圆形、梯形等图形的面积公式。
4.4 距离：两点间的距离、线段的长度等。
4.5 比例：相似图形、全等图形的比例关系等。
4.6 比例尺：图上的距离与实际距离的比例关系。
五、数学符号的重点标记5.1 集合符号：集合、交集、并集、补集等。
5.2 函数符号：函数、自变量、因变量、函数图像等。
5.3 关系符号：大于、小于、等于、不等、包含、包含于等。
5.4 运算符号：加、减、乘、除、乘方、开方等。
matlab图像处理函数大全
matlab图像处理函数大全Matlab是一种强大的科学计算软件，广泛应用于各个领域，包括图像处理。
在Matlab中，有许多内置的图像处理函数，可以帮助我们实现各种图像处理任务。
本文将介绍一些常用的Matlab图像处理函数，帮助您更好地理解和运用这些函数。
1. imread函数imread函数用于读取图像文件，并将其存储为Matlab的图像矩阵。
它可以读取多种图像格式，如JPEG、PNG、BMP等。
例如，可以使用以下代码读取名为"image.jpg"的图像文件：```matlabimage = imread('image.jpg');```2. imshow函数imshow函数用于显示图像。
它可以接受一个图像矩阵作为输入，并将其显示在Matlab的图像窗口中。
例如，可以使用以下代码显示之前读取的图像：```matlabimshow(image);```3. imresize函数imresize函数用于调整图像的大小。
它可以接受一个图像矩阵和目标大小作为输入，并返回调整大小后的图像矩阵。
例如，可以使用以下代码将图像调整为200x200的大小：```matlabresized_image = imresize(image, [200, 200]);```4. rgb2gray函数rgb2gray函数用于将彩色图像转换为灰度图像。
它可以接受一个彩色图像矩阵作为输入，并返回一个灰度图像矩阵。
例如，可以使用以下代码将彩色图像转换为灰度图像：```matlabgray_image = rgb2gray(image);```5. imadjust函数imadjust函数用于调整图像的对比度和亮度。
它可以接受一个灰度图像矩阵和目标对比度和亮度范围作为输入，并返回调整后的图像矩阵。
例如，可以使用以下代码增加图像的对比度和亮度：```matlabadjusted_image = imadjust(gray_image, [0.2, 0.8], [0, 1]);```6. imfilter函数imfilter函数用于对图像进行滤波操作。
城市国土空间监测数字正射影像生产技术探讨刘雅丽
城市国土空间监测数字正射影像生产技术探讨刘雅丽发布时间：2023-05-08T10:01:28.588Z 来源：《工程建设标准化》2023年5期作者：刘雅丽[导读] 地理国情监测是一项重大的国情国力调查,是对全国地理信息基础数据的全面细化和完善。
新疆天地经纬测绘工程有限公司 830000摘要：地理国情监测是一项重大的国情国力调查,是对全国地理信息基础数据的全面细化和完善。
因此,国务院对地理国情监测工作提出了常态化的要求。
在城市每年对地理国情监测成果数据进行更新的过程中，数字正射影像数据是监测成果的重要组成部分.也是地理国情监测项目最主要的调查数据源。
因此,如何快速,高效、高质量地制作数字正射影像,是完成地理国情监测项目的根本保障。
本文以城市地理国情监测数字正射影像快速生产为例,详细介绍基于DEMX软件制作数字正射影像的方法及流程,探索多景影像数据快速、高精度的纠正技术。
关键词：城市地理国情监测;正射影像;DEMXL引言地理国情关系着一个国家的自然资源开发利用，关系着社会经济发展战略，关系着重大方针政策和长远发展的基本方向。
2015年，我国已成功地完成了第一次地理国情普查，为了更好地了解国势、掌握国情、制定国策，国务院对地理国情监测工作提出了常态化的要求。
辽宁省在进行基础地理国情调查的同时，也在不断地运用现代测绘技术手段，为数据的收集、处理和分析提供了基本的保证。
地理国情成果资料主要有：数字正射影像资料、地面覆盖资料、地理国情要素资料、解析样例资料、专题资料等。
数字正射影像（DOM）数据是地理国情成果数据中最重要的组成部分，也是最主要的调查数据源。
它具有精度高、现势性强、信息丰富、直观逼真、获取方便等特点，既具有地图的几何精度又具有图像的特点，因此具有良好的判读性、预测性和管理性。
DOM是地学国情监测工程中最重要的资料来源，其质量与准确度是决定工程成败的关键。
每年都在深入开展地理国情监测计划。
随着遥感数据分辨率的不断提高和数据量的不断增加，传统的遥感数据校正软件及工作方式存在着人为干预多、误码率高、耗时长等问题，严重制约了遥感数据的应用。
景观面积测量方法
景观面积测量方法景观面积测量方法主要分为实地测量和数字化测量两种，以下是其中50条关于景观面积测量方法的详细描述：1. 实地测量方法：通过在实地使用测量工具进行测量，例如测量带、测距仪等。
2. 数字化测量方法：利用地理信息系统（GIS）、遥感影像、无人机等技术进行数字化测量。
3. 利用卫星影像：利用高分辨率卫星影像进行景观面积的测量，通过图像处理软件进行像元计数和面积估算。
4. 高精度GPS测量：利用高精度GPS进行实时定位和测量，通过差分GPS技术提高测量精度。
5. 使用激光测距仪：利用激光测距仪进行快速、精确的测量，适用于复杂地形和建筑物的测量。
6. 面积比例尺法：通过在地图上设置比例尺，计算实际面积与地图上的面积比例，从而估算景观面积。
7. 图像处理软件测量：利用图像处理软件如ArcGIS、ENVI等进行遥感影像的分析和面积测量。
8. 通过数字高程模型（DEM）进行测量：利用DEM数据进行地形分析，计算地表面积。
9. 利用三角形测量法：通过设置三角形网格进行测量，计算多边形面积的方法。
10. 利用无人机进行测量：使用无人机携带相机进行航拍，并通过图像处理软件进行面积的测量。
11. 网格化面积计算法：将测量区域进行网格化划分，计算出每个小网格的面积，然后累加得出总面积。
12. 利用全站仪进行测量：通过全站仪进行高程和坐标的测量，进而计算出景观面积。
13. 通过地面控制点进行校正和定位：通过设置地面控制点，校正遥感影像的畸变，提高面积测量的准确性。
14. 利用光栅数据进行测量：利用遥感光栅数据进行景观面积的测量和分析。
15. 使用面积测量软件进行测量：利用专业的面积测量软件进行景观面积的测量和分析。
16. 手持式测距仪进行测量：对小范围的景观进行快速测量，适用于野外调查。
17. 基于建筑物轮廓的测量方法：通过测量建筑物轮廓的方式，计算出建筑物占地面积。
18. 横断面法进行测量：通过勘测测量，计算横截面积，然后累加得出总面积。
影像测量仪使用说明
影像测量仪使用说明第一部分：产品概述影像测量仪是一种通过数字图像技术实现测量的设备，它可以用于工业、医疗、科研等领域。
本影像测量仪采用先进的图像处理算法和高分辨率的传感器，能够实现高精度、高效率的测量。
本使用说明将介绍影像测量仪的基本操作和功能，帮助用户熟悉和正确使用该设备。
第二部分：产品特点1.高精度：影像测量仪采用高分辨率的传感器，能够实现高精度的测量。
2.多功能：本设备可以实现多种测量功能，包括长度测量、面积测量、圆直径测量等。
3.高效率：影像测量仪具有快速响应的速度，能够在短时间内完成大量测量任务。
4.易于使用：本设备采用简单直观的操作界面，用户只需按照指示操作即可完成测量。
第三部分：设备准备1.将影像测量仪连接到电源，并确保电源正常。
2.打开显示屏，启动测量软件。
3.将待测物品放置在测量台上，并调整合适的放置位置。
第四部分：基本操作1.打开测量软件后，会出现主界面，界面上会显示实时图像。
2.点击“新建测量”按钮，进入测量模式。
3.在实时图像中选择一个待测点，点击鼠标左键进行标记。
4.根据测量需求，在实时图像中选择其他待测点，并进行标记。
5.点击“测量”按钮，软件会根据标记的点位进行测量计算。
第五部分：测量功能1.长度测量：在实时图像中标记起始点和终止点，软件会根据标记的点位计算长度。
2.面积测量：在实时图像中选择物体边界，并进行闭合标记，软件会根据标记的区域计算面积。
3.圆直径测量：在实时图像中选择圆的边界，并进行闭合标记，软件会根据标记的区域计算圆的直径。
第六部分：注意事项1.在进行测量之前，应确保测量台和待测物品处于平稳状态，以避免测量误差。
2.在进行标记时，应尽量选择清晰明确的标记点位，以提高测量的准确性。
3.在进行测量时，需注意避免手部晃动和环境光线干扰，以影响测量的准确性。
第七部分：故障排除1.如果影像测量仪无法启动，请检查电源是否连接正常，并重新启动设备。
2.如果软件无法识别图像，请检查设备的连接是否稳固，并重新启动软件。
ImageJ在荧光照片分析中的应用介绍
Image J在显微成像中的应用介绍1、关于Image JImageJ是一个基于java的公共的图像处理软件，它是由National Institutes of Health 开发的。
可运行于Microsoft Windows，Mac OS，Mac OS X，Linux，和Sharp Zaurus PDA等多种平台。
其基于java 的特点，使得它编写的程序能以applet等方式分发。
ImageJ能够显示，编辑，分析，处理，保存，打印8 位，16 位，32 位的图片，支持TIFF, PNG, GIF, JPEG, BMP, DICOM, FITS等多种格式。
ImageJ 支持图像栈（stack）功能，即在一个窗口里以多线程的形式层叠多个图像，并行处理。
只要内存允许，ImageJ 能打开任意多的图像进行处理。
除了基本的图像操作，比如缩放，旋转，扭曲，平滑处理外，ImageJ还能进行图片的区域和像素统计，间距，角度计算，能创建柱状图和剖面图，进行傅里叶变换。
下载地址：/ij/download.html2、Image 界面界面分为：菜单栏，工具栏和状态栏。
菜单栏菜单栏从左至右分别是：文件，编辑，图形，处理，分析，插件，窗口，帮助。
文件和office word 等软件类似，主要有文件打开，关闭，保存等功能，比较特殊的一个功能是恢复功能（revert），可以直接回到上次保存过的状态。
由于编辑菜单里的取消功能（undo）只能回退一步，所以revert 有时会很有帮助。
编辑Undo, Cut, Copy, Copy to system, Paste, Paste Control.., Clear, Clear Outside, Fill, Draw, Invert, Selection, Options.图像Type（可改变图片格式，如彩色变灰度）, Adjust, Show info, Properties, Color, Stacks, Hyperstacks, Crop, Duplicate.., Rename, Scale, Transform, Zoom, Overlay, Lookup Tables.处理Smooth, Sharpen, Find Edges, Find Maxima, Enhance Contrast, Noise, Shadows, Binary, Math, FFT, Filters, Batch, Image calculator, Subtract Backgroud, Repeat Command.分析Measure, Analyze Particles, Summarize, Distibution, Label, Clear Results, Set measurements, Set Scale, Calibrate, Histogram, Plot Profile, Surface Plot, Gels, Tools.窗口和帮助工具栏工具栏从左至右分别是4种区域选择工具，直线选择工具，角度工具，点工具，魔棒，文字，放大镜，拖手，颜色吸管，动作宏，菜单宏，绘图工具等（颜色吸管以后的内容可以变化，通过点击最右边的>> 按钮选择需要的栏目。
地积的计算方法
地积的计算方法地积是指一个地区的面积大小，通常用于衡量土地的大小。
计算地积的方法包括测量法、制图法、遥感法和数学模型法等。
以下是关于地积计算方法的详细介绍。
一、测量法测量法是最常用的地积计算方法之一。
它通过实地测量土地边界的长度和角度，然后利用三角测量或其他测量方法计算出土地面积。
测量法的基本步骤如下：1.确定测量范围：首先确定要测量的土地范围，并标记出土地的边界点。
2.进行测量：使用测量仪器，如全站仪或经纬仪，测量出土地的各个边界的长度和角度。
3.计算面积：使用计算公式，如海涅公式、角面积公式或多边形面积公式，根据测量得到的数据计算出土地的面积。
4.校正误差：对于测量中可能存在的误差，需要进行校正，以提高测量结果的准确性。
5.整理结果：将计算得到的地积结果整理为适当的格式，以便于后续使用和分析。
二、制图法制图法是通过绘制地图来计算地积的一种方法。
它基于地图比例尺和测量的地物长度，通过将地物在地图上进行投影，然后计算投影面积来估算地积。
制图法的基本步骤如下：1.绘制地图：首先，在适当的比例尺上绘制地图，标记出土地的边界和相关地物。
2.测量地物长度：使用测量工具，如地图测量尺、曲线尺或量角器，测量地图上各地物的长度。
3.计算投影面积：根据比例尺和测量的地物长度，计算地图上各地物的投影面积。
4.累积面积：将地图上各地物的投影面积进行累积，得到整个土地的面积。
5.校正误差：对于地图尺度和测量误差可能引入的误差，需要进行校正，以提高计算结果的准确性。
三、遥感法遥感法是利用遥感技术获取地物信息，并利用数字图像处理和分析方法来计算地积的一种方法。
它使用航空或卫星遥感图像，通过图像解译和分类来提取土地边界，并计算各类地物的面积。
遥感法的基本步骤如下：1.获取遥感图像：利用航空或卫星遥感技术获取高分辨率的遥感图像。
2.图像解译和分类：对遥感图像进行解译和分类，将土地区域和其他地物进行区分和分类。
3.地物面积计算：根据分类结果，计算各类地物的面积，得到土地的总面积。
python计算不规则图形面积算法
python计算不规则图形⾯积算法介绍：⼤三上做⼀个医学影像识别的项⽬，医⽣在原图上⽤红笔标记病灶点，通过记录红⾊的坐标位置可以得到病灶点的外接矩形，但是后续会涉及到红圈内的⾯积在外接矩形下的占⽐问题，有些外接矩形内有多个红⾊标记，在使⽤⽹上的opencv的fillPoly填充效果⾮常不理想，还有类似python计算任意多边形⽅法也不理想的情况下，⾃⼰探索出的⼀种效果还不错的计算多圈及不规则图形的⾯积的算法。
医⽣提供的病灶标记图和原图，⼤部分长这样但也有⼀些多圈情况很明显，这些图⽚都是⾮常需要计算⾯积占⽐的，对样本需要筛选通过百度，⽤opencv的填充来计算⾯积，⼀部分效果很差，单圈画不全，多圈都是错（⽤将⾯积计算结果上⾊，⽅便观察）通过此算法之后，⽆论单圈，多圈，⾯积计算准确度提⾼许多能较为准确的计算出不规则图形的⾯积正⽂:算法的思想很简单，遍历图⽚每⼀列，通过⾊差判断是否遇到标记圈，将坐标全部记录，对每⼀列的坐标都进⾏最⼩⾏和最⼤⾏记录，确定每⼀列的最⼩和最⼤的坐标，然后上⾊（类似opencv的fillPoly的实现，但是细节有些区别），只是这样效果并不好，将图⽚旋转90度，再做⼀边，将两个图⽚的结果放在⼀起做与操作，得到结果就能很好的处理多圈的标记问题和多算⾯积的问题（⽐如上⾯的08-LM），算法实现全程只⽤pillow库⾸先先⽤屏幕拾⾊器获取⽬标颜⾊的rgb值，我这种情况下就是（237，28，36），前期截取外接矩形也是要这⼀步的，颜⾊也⼀致1def pixel_wanted(pix):2return pix==(237,28, 36)每⼀列都设定翻转位初始为False，如果上⼀个像素点不是⽬标⾊，当前是⽬标⾊则开始记录，⼀旦不是⽬标⾊，停⽌检测top_Pixel都设定为⿊⾊（0，0，0）因为有图⽚最上⽅就是⽬标⾊，导致判定出问题，直接让最上⾯的像素初始化是⿊⾊coordinate_List记录了所有符合的点坐标1 coordinate_List = []2 top_Pixel = (0,0,0)3for x in range(im.size[0]):4 flag = False #初始化每⼀列翻转位为False5for y in range(im.size[1]):6 current_pixel = im.getpixel((x,y))7 last_pixel = im.getpixel((x,y-1)) if y>0 else top_Pixel8#翻转判定9if pixel_wanted(current_pixel) and \10not pixel_wanted(last_pixel):11 flag = True12if flag and not pixel_wanted(current_pixel):13 flag = False14if(flag):15 coordinate_List.append((x,y))coordinate_List中的点如下图然后就是将上⾯获得coordinate列表进⾏处理将coordinate列表中每⼀列的最⼩坐标和最⼤坐标进⾏记录因为每⼀列记录的数量并不确定（应该可以在上⼀步改进⼀下），所以需要遍历多次⾸先找到第⼀个列出现的坐标，将它的⾏信息记录（⾏信息最⼩确定），然后遍历出全部的同列的坐标，⽐较⾏坐标，如果⼤的就将最⼤的代替（⾏信息最⼤确定），⽤⼀个新的列表记录数据1 coordinate_Min_Max_List = []2#找最⼩最⼤3for i in range(im.size[0]):4 min=-15 max=-16for coordinate in coordinate_List:7if coordinate[0] == i:8 min = coordinate[1]9 max = coordinate[1]10break11for coordinate in coordinate_List:12if coordinate[0] == i:13if coordinate[1]>max:14 max = coordinate[1]15 coordinate_Min_Max_List.append(min)16 coordinate_Min_Max_List.append(max)其中要将min和max都初始化为⼀个坐标不存在的值⽐如-1，为了在下⼀步多圈且有空隙情况下，不会出现残影现象，如下图上⼀步的最后得到⼀个列表，第n列的最⼩⾏和最⼤⾏分别是第2n和2n+1元素，结果中的-1，为了让下⼀步不会画进去然后就是绘制图⽚了，每⼀列将列表中对应的最⼩⾏到最⼤⾏涂满1#上⾊2for x in range(im.size[0]):3for y in range(im.size[1]):4 min = coordinate_Min_Max_List[x*2]5 max = coordinate_Min_Max_List[x*2+1]6if min<y<max:7 im.putpixel((x,y),(0,255,0))8else:9#可以把⾮红圈的上掩膜遮住10pass⾄此，就是类似opencv的算法实现，虽然还差翻转做与操作，但是已经⽐opencv⽣成的效果好，写成函数后续调⽤，然后就是简单的翻转90度，再调⽤⼀次这个函数再做⼀遍1def Cal_S(im):2 im_0 = im.rotate(0)3 im_90 = im.rotate(90, expand=True)45 im_0 = fillPoly(im_0)6 im_90 = fillPoly(im_90)7 im_90 = im_90.rotate(-90, expand=True)89 i=010for x in range(im.size[0]):11for y in range(im.size[1]):12if(im_0.getpixel((x,y))==(0,255,0) and13 im_90.getpixel((x,y))==(0,255,0)):14 im.putpixel((x,y),(0,255,0))15 i+=116return i/(im.size[0]*im.size[1])做两遍的效果图但现在的话误差已经降低⾮常多了，这些极其个别的⼗字现象可以⼿动把原图切割⼀下，或者⼲脆不处理了所有代码，画出绿图⽚为了⽅便直观的查看，函数中可以把图⽚顺便保存⼀下，总体看⼀下效果 1from PIL import Image23def pixel_wanted(pix):4return pix==(237,28, 36)56def fillPoly(im):7 coordinate_List = []89 top_Pixel = (0,0,0)10for x in range(im.size[0]):11 flag = False #初始化每⼀列翻转位为False12for y in range(im.size[1]):13 current_pixel = im.getpixel((x,y))14 last_pixel = im.getpixel((x,y-1)) if y>0 else top_Pixel15#翻转判定16if pixel_wanted(current_pixel) and \17not pixel_wanted(last_pixel):18 flag = True19if flag and not pixel_wanted(current_pixel):20 flag = False21if(flag):22 coordinate_List.append((x,y))23 coordinate_Min_Max_List = []24#找最⼩最⼤25for i in range(im.size[0]):26 min=-127 max=-128for coordinate in coordinate_List:29if coordinate[0] == i:30 min = coordinate[1]31 max = coordinate[1]32break33for coordinate in coordinate_List:34if coordinate[0] == i:35if coordinate[1]>max:36 max = coordinate[1]37 coordinate_Min_Max_List.append(min)38 coordinate_Min_Max_List.append(max)39#上⾊40for x in range(im.size[0]):41for y in range(im.size[1]):42 min = coordinate_Min_Max_List[x*2]43 max = coordinate_Min_Max_List[x*2+1] 44if min<y<max:45 im.putpixel((x,y),(0,255,0))46else:47#可以把⾮红圈的上掩膜遮住48pass49return im5051def Cal_S(im):52 im_0 = im.rotate(0)53 im_90 = im.rotate(90, expand=True)5455 im_0 = fillPoly(im_0)56 im_90 = fillPoly(im_90)57 im_90 = im_90.rotate(-90, expand=True)5859 i=060for x in range(im.size[0]):61for y in range(im.size[1]):62if(im_0.getpixel((x,y))==(0,255,0) and63 im_90.getpixel((x,y))==(0,255,0)):64 im.putpixel((x,y),(0,255,0))65 i+=166return i/(im.size[0]*im.size[1])。
halcon 取最大区域算子
马丁·路德·金英文演讲：我已达至峰顶马丁·路德·金是著名的美国民权运动领袖，今天给大家分享一篇马丁路德金在临死前一天的精彩演讲，希望对大家有所帮助。
马丁·路德·金英文演讲：我已达至峰顶Thank you very kindly, my friends. As I listened to Ralph Abernathy and his eloquent and generous introduction and then thought about myself, I wondered who he was talking about. It's always good to have your closest friend and associate to say something good about you. And Ralph Abernathy is the best friend that I have in the world. I'm delighted to see each of you here tonight in spite of a storm warning. You reveal that you are determined to go on anyhow.Something is happening in Memphis; something is happening in our world. And you know, if I were standing at the beginning of time, with the possibility of taking a kind of general and panoramic view of the whole of human history up to now, and the Almighty said to me, "Martin Luther King, which age would you like to live in?" I would take my mental flight by Egypt and I would watch God's children in their magnificent trek from the dark dungeons of Egypt through, or rather across the Red Sea, through the wilderness on toward the promised land. And in spite of its magnificence, I wouldn't stop there.I would move on by Greece and take my mind to Mount Olympus. And I would see Plato, Aristotle, Socrates, Euripides and Aristophanesassembled around the Parthenon. And I would watch them around the Parthenon as they discussed the great and eternal issues of reality. But I wouldn't stop there.I would go on, even to the great heyday of the Roman Empire. And I would see developments around there, through various emperors and leaders. But I wouldn't stop there.I would even come up to the day of the Renaissance, and get a quick picture of all that the Renaissance did for the cultural and aesthetic life of man. But I wouldn't stop there.I would even go by the way that the man for whom I am named had his habitat. And I would watch Martin Luther as he tacked his ninety-five theses on the door at the church of Wittenberg. But I wouldn't stop there.I would come on up even to 1863, and watch a vacillating President by the name of Abraham Lincoln finally come to the conclusion that he had to sign the Emancipation Proclamation. But I wouldn't stop there.I would even come up to the early thirties, and see a man grappling with the problems of the bankruptcy of his nation. And come with an eloquent cry that we have nothing to fear but "fear itself." But I wouldn't stop there.Strangely enough, I would turn to the Almighty, and say, "If you allow me to live just a few years in the second half of the 20th century, Iwill be happy."Now that's a strange statement to make, because the world is all messed up. The nation is sick. Trouble is in the land; confusion all around. That's a strange statement. But I know, somehow, that only when it is dark enough can you see the stars. And I see God working in this period of the twentieth century in a way that men, in some strange way, are responding.Something is happening in our world. The masses of people are rising up. And wherever they are assembled today, whether they are in Johannesburg, South Africa; Nairobi, Kenya; Accra, Ghana; New York City; Atlanta, Georgia; Jackson, Mississippi; or Memphis, Tennessee -- the cry is always the same: "We want to be free."And another reason that I'm happy to live in this period is that we have been forced to a point where we are going to have to grapple with the problems that men have been trying to grapple with through history, but the demands didn't force them to do it. Survival demands that we grapple with them. Men, for years now, have been talking about war and peace. But now, no longer can they just talk about it. It is no longer a choice between violence and nonviolence in this world; it's nonviolence or nonexistence. That is where we are today.And also in the human rights revolution, if something isn't done, and done in a hurry, to bring the colored peoples of the world out oftheir long years of poverty, their long years of hurt and neglect, the whole world is doomed. Now, I'm just happy that God has allowed me to live in this period to see what is unfolding. And I'm happy that He's allowed me to be in Memphis.I can remember -- I can remember when Negroes were just going around as Ralph has said, so often, scratching where they didn't itch, and laughing when they were not tickled. But that day is all over. We mean business now, and we are determined to gain our rightful place in God's world.And that's all this whole thing is about. We aren't engaged in any negative protest and in any negative arguments with anybody. We are saying that we are determined to be men. We are determined to be people. We are saying -- We are saying that we are God's children. And that we are God's children, we don't have to live like we are forced to live.Now, what does all of this mean in this great period of history? It means that we've got to stay together. We've got to stay together and maintain unity. You know, whenever Pharaoh wanted to prolong the period of slavery in Egypt, he had a favorite, favorite formula for doing it. What was that? He kept the slaves fighting among themselves. But whenever the slaves get together, something happens in Pharaoh's court, and he cannot hold the slaves in slavery. When the slaves get together,that's the beginning of getting out of slavery. Now let us maintain unity.Secondly, let us keep the issues where they are. The issue is injustice. The issue is the refusal of Memphis to be fair and honest in its dealings with its public servants, who happen to be sanitation workers. Now, we've got to keep attention on that. That's always the problem with a little violence. You know what happened the other day, and the press dealt only with the window-breaking. I read the articles. They very seldom got around to mentioning the fact that one thousand, three hundred sanitation workers are on strike, and that Memphis is not being fair to them, and that Mayor Loeb is in dire need of a doctor. They didn't get around to that.Now we're going to march again, and we've got to march again, in order to put the issue where it is supposed to be -- and force everybody to see that there are thirteen hundred of God's children here suffering, sometimes going hungry, going through dark and dreary nights wondering how this thing is going to come out. That's the issue. And we've got to say to the nation: We know how it's coming out. For when people get caught up with that which is right and they are willing to sacrifice for it, there is no stopping point short of victory.We aren't going to let any mace stop us. We are masters in our nonviolent movement in disarming police forces; they don't know what to do. I've seen them so often. I remember in Birmingham, Alabama,when we were in that majestic struggle there, we would move out of the 16th Street Baptist Church day after day; by the hundreds we would move out. And Bull Connor would tell them to send the dogs forth, and they did come; but we just went before the dogs singing, "Ain't gonna let nobody turn me around."Bull Connor next would say, "Turn the fire hoses on." And as I said to you the other night, Bull Connor didn't know history. He knew a kind of physics that somehow didn't relate to the transphysics that we knew about. And that was the fact that there was a certain kind of fire that no water could put out. And we went before the fire hoses; we had known water. If we were Baptist or some other denominations, we had been immersed. If we were Methodist, and some others, we had been sprinkled, but we knew water. That couldn't stop us.And we just went on before the dogs and we would look at them; and we'd go on before the water hoses and we would look at it, and we'd just go on singing "Over my head I see freedom in the air." And then we would be thrown in the paddy wagons, and sometimes we were stacked in there like sardines in a can. And they would throw us in, and old Bull would say, "Take 'em off," and they did; and we would just go in the paddy wagon singing, "We Shall Overcome." And every now and then we'd get in jail, and we'd see the jailers looking through the windows being moved by our prayers, and being moved by our words and oursongs. And there was a power there which Bull Connor couldn't adjust to; and so we ended up transforming Bull into a steer, and we won our struggle in Birmingham. Now we've got to go on in Memphis just like that. I call upon you to be with us when we go out Monday.Now about injunctions: We have an injunction and we're going into court tomorrow morning to fight this illegal, unconstitutional injunction. All we say to America is, "Be true to what you said on paper." If I lived in China or even Russia, or any totalitarian country, maybe I could understand some of these illegal injunctions. Maybe I could understand the denial of certain basic First Amendment privileges, because they hadn't committed themselves to that over there. But somewhere I read of the freedom of assembly. Somewhere I read of the freedom of speech. Somewhere I read of the freedom of press. Somewhere I read that the greatness of America is the right to protest for right. And so just as I say, we aren't going to let dogs or water hoses turn us around, we aren't going to let any injunction turn us around. We are going on.We need all of you. And you know what's beautiful to me is to see all of these ministers of the Gospel. It's a marvelous picture. Who is it that is supposed to articulate the longings and aspirations of the people more than the preacher? Somehow the preacher must have a kind of fire shut up in his bones. And whenever injustice is around he tell it. Somehow the preacher must be an Amos, and saith, "When God speakswho can but prophesy?" Again with Amos, "Let justice roll down like waters and righteousness like a mighty stream." Somehow the preacher must say with Jesus, "The Spirit of the Lord is upon me, because he hath anointed me," and he's anointed me to deal with the problems of the poor."And I want to commend the preachers, under the leadership of these noble men: James Lawson, one who has been in this struggle for many years; he's been to jail for struggling; he's been kicked out of Vanderbilt University for this struggle, but he's still going on, fighting for the rights of his people. Reverend Ralph Jackson, Billy Kiles; I could just go right on down the list, but time will not permit. But I want to thank all of them. And I want you to thank them, because so often, preachers aren't concerned about anything but themselves. And I'm always happy to see a relevant ministry.It's all right to talk about "long white robes over yonder," in all of its symbolism. But ultimately people want some suits and dresses and shoes to wear down here! It's all right to talk about "streets flowing with milk and honey," but God has commanded us to be concerned about the slums down here, and his children who can't eat three square meals a day. It's all right to talk about the new Jerusalem, but one day, God's preacher must talk about the new New York, the new Atlanta, the new Philadelphia, the new Los Angeles, the new Memphis, Tennessee. This iswhat we have to do.Now the other thing we'll have to do is this: Always anchor our external direct action with the power of economic withdrawal. Now, we are poor people. Individually, we are poor when you compare us with white society in America. We are poor. Never stop and forget that collectively -- that means all of us together -- collectively we are richer than all the nations in the world, with the exception of nine. Did you ever think about that? After you leave the United States, Soviet Russia, Great Britain, West Germany, France, and I could name the others, the American Negro collectively is richer than most nations of the world. We have an annual income of more than thirty billion dollars a year, which is more than all of the exports of the United States, and more than the national budget of Canada. Did you know that? That's power right there, if we know how to pool it.We don't have to argue with anybody. We don't have to curse and go around acting bad with our words. We don't need any bricks and bottles. We don't need any Molotov cocktails. We just need to go around to these stores, and to these massive industries in our country, and say, "God sent us by here, to say to you that you're not treating his children right. And we've come by here to ask you to make the first item on your agenda fair treatment, where God's children are concerned. Now, if you are not prepared to do that, we do have an agenda that we must follow.And our agenda calls for withdrawing economic support from you."And so, as a result of this, we are asking you tonight, to go out and tell your neighbors not to buy Coca-Cola in Memphis. Go by and tell them not to buy Sealtest milk. Tell them not to buy -- what is the other bread? -- Wonder Bread. And what is the other bread company, Jesse? Tell them not to buy Hart's bread. As Jesse Jackson has said, up to now, only the garbage men have been feeling pain; now we must kind of redistribute the pain. We are choosing these companies because they haven't been fair in their hiring policies; and we are choosing them because they can begin the process of saying they are going to support the needs and the rights of these men who are on strike. And then they can move on town -- downtown and tell Mayor Loeb to do what is right.But not only that, we've got to strengthen black institutions. I call upon you to take your money out of the banks downtown and deposit your money in Tri-State Bank. We want a "bank-in" movement in Memphis. Go by the savings and loan association. I'm not asking you something that we don't do ourselves at SCLC. Judge Hooks and others will tell you that we have an account here in the savings and loan association from the Southern Christian Leadership Conference. We are telling you to follow what we are doing. Put your money there. You have six or seven black insurance companies here in the city of Memphis. Take out your insurance there. We want to have an "insurance-in."Now these are some practical things that we can do. We begin the process of building a greater economic base. And at the same time, we are putting pressure where it really hurts. I ask you to follow through here.Now, let me say as I move to my conclusion that we've got to give ourselves to this struggle until the end. Nothing would be more tragic than to stop at this point in Memphis. We've got to see it through. And when we have our march, you need to be there. If it means leaving work, if it means leaving school -- be there. Be concerned about your brother. You may not be on strike. But either we go up together, or we go down together.Let us develop a kind of dangerous unselfishness. One day a man came to Jesus, and he wanted to raise some questions about some vital matters of life. At points he wanted to trick Jesus, and show him that he knew a little more than Jesus knew and throw him off base....Now that question could have easily ended up in a philosophical and theological debate. But Jesus immediately pulled that question from mid-air, and placed it on a dangerous curve between Jerusalem and Jericho. And he talked about a certain man, who fell among thieves. You remember that a Levite and a priest passed by on the other side. They didn't stop to help him. And finally a man of another race came by. He got down from his beast, decided not to be compassionate by proxy. Buthe got down with him, administered first aid, and helped the man in need. Jesus ended up saying, this was the good man, this was the great man, because he had the capacity to project the "I" into the "thou," and to be concerned about his brother.Now you know, we use our imagination a great deal to try to determine why the priest and the Levite didn't stop. At times we say they were busy going to a church meeting, an ecclesiastical gathering, and they had to get on down to Jerusalem so they wouldn't be late for their meeting. At other times we would speculate that there was a religious law that "One who was engaged in religious ceremonials was not to touch a human body twenty-four hours before the ceremony." And every now and then we begin to wonder whether maybe they were not going down to Jerusalem -- or down to Jericho, rather to organize a "Jericho Road Improvement Association." That's a possibility. Maybe they felt that it was better to deal with the problem from the causal root, rather than to get bogged down with an individual effect.But I'm going to tell you what my imagination tells me. It's possible that those men were afraid. You see, the Jericho road is a dangerous road. I remember when Mrs. King and I were first in Jerusalem. We rented a car and drove from Jerusalem down to Jericho. And as soon as we got on that road, I said to my wife, "I can see why Jesus used this as the setting for his parable." It's a winding, meandering road. It's reallyconducive for ambushing. You start out in Jerusalem, which is about 1200 miles -- or rather 1200 feet above sea level. And by the time you get down to Jericho, fifteen or twenty minutes later, you're about 2200 feet below sea level. That's a dangerous road. In the days of Jesus it came to be known as the "Bloody Pass." And you know, it's possible that the priest and the Levite looked over that man on the ground and wondered if the robbers were still around. Or it's possible that they felt that the man on the ground was merely faking. And he was acting like he had been robbed and hurt, in order to seize them over there, lure them there for quick and easy seizure. And so the first question that the priest asked -- the first question that the Levite asked was, "If I stop to help this man, what will happen to me?" But then the Good Samaritan came by. And he reversed the question: "If I do not stop to help this man, what will happen to him?"That's the question before you tonight. Not, "If I stop to help the sanitation workers, what will happen to my job. Not, "If I stop to help the sanitation workers what will happen to all of the hours that I usually spend in my office every day and every week as a pastor?" The question is not, "If I stop to help this man in need, what will happen to me?" The question is, "If I do not stop to help the sanitation workers, what will happen to them?" That's the question.Let us rise up tonight with a greater readiness. Let us stand with agreater determination. And let us move on in these powerful days, these days of challenge to make America what it ought to be. We have an opportunity to make America a better nation. And I want to thank God, once more, for allowing me to be here with you.You know, several years ago, I was in New York City autographing the first book that I had written. And while sitting there autographing books, a demented black woman came up. The only question I heard from her was, "Are you Martin Luther King?" And I was looking down writing, and I said, "Yes." And the next minute I felt something beating on my chest. Before I knew it I had been stabbed by this demented woman. I was rushed to Harlem Hospital. It was a dark Saturday afternoon. And that blade had gone through, and the X-rays revealed that the tip of the blade was on the edge of my aorta, the main artery. And once that's punctured, your drowned in your own blood -- that's the end of you.It came out in the New York Times the next morning, that if I had merely sneezed, I would have died. Well, about four days later, they allowed me, after the operation, after my chest had been opened, and the blade had been taken out, to move around in the wheel chair in the hospital. They allowed me to read some of the mail that came in, and from all over the states and the world, kind letters came in. I read a few, but one of them I will never forget. I had received one from the Presidentand the Vice-President. I've forgotten what those telegrams said. I'd received a visit and a letter from the Governor of New York, but I've forgotten what that letter said. But there was another letter that came from a little girl, a young girl who was a student at the White Plains High School. And I looked at that letter, and I'll never forget it. It said simply, Dear Dr. King,I am a ninth-grade student at the White Plains High School."And she said,While it should not matter, I would like to mention that I'm a white girl. I read in the paper of your misfortune, and of your suffering. And I read that if you had sneezed, you would have died. And I'm simply writing you to say that I'm so happy that you didn't sneeze.And I want to say tonight -- I want to say tonight that I too am happy that I didn't sneeze. Because if I had sneezed, I wouldn't have been around here in 1960, when students all over the South started sitting-in at lunch counters. And I knew that as they were sitting in, they were really standing up for the best in the American dream, and taking the whole nation back to those great wells of democracy which were dug deep by the Founding Fathers in the Declaration of Independence and the Constitution.If I had sneezed, I wouldn't have been around here in 1961, when we decided to take a ride for freedom and ended segregation ininter-state travel.If I had sneezed, I wouldn't have been around here in 1962, when Negroes in Albany, Georgia, decided to straighten their backs up. And whenever men and women straighten their backs up, they are going somewhere, because a man can't ride your back unless it is bent.If I had sneezed -- If I had sneezed I wouldn't have been here in 1963, when the black people of Birmingham, Alabama, aroused the conscience of this nation, and brought into being the Civil Rights Bill.If I had sneezed, I wouldn't have had a chance later that year, in August, to try to tell America about a dream that I had had.If I had sneezed, I wouldn't have been down in Selma, Alabama, to see the great Movement there.If I had sneezed, I wouldn't have been in Memphis to see a community rally around those brothers and sisters who are suffering.I'm so happy that I didn't sneeze.And they were telling me --. Now, it doesn't matter, now. It really doesn't matter what happens now. I left Atlanta this morning, and as we got started on the plane, there were six of us. The pilot said over the public address system, "We are sorry for the delay, but we have Dr. Martin Luther King on the plane. And to be sure that all of the bags were checked, and to be sure that nothing would be wrong with on the plane, we had to check out everything carefully. And we've had the planeprotected and guarded all night."And then I got into Memphis. And some began to say the threats, or talk about the threats that were out. What would happen to me from some of our sick white brothers?Well, I don't know what will happen now. We've got some difficult days ahead. But it really doesn't matter with me now, because I've been to the mountaintop.And I don't mind.Like anybody, I would like to live a long life. Longevity has its place. But I'm not concerned about that now. I just want to do God's will. And He's allowed me to go up to the mountain. And I've looked over. And I've seen the Promised Land. I may not get there with you. But I want you to know tonight, that we, as a people, will get to the promised land!mlkmountaintop3.JPGAnd so I'm happy, tonight.I'm not worried about anything.I'm not fearing any man!Mine eyes have seen the glory of the coming of the Lord!。
分水岭算法
分水岭算法所谓的分水岭算法有很多实现算法，例如拓扑，形态，洪水模拟和降水模拟。
分水岭算法根据分水岭的组成考虑图像分割。
在现实中，我们可以或可以想象有高山和湖泊，那么这必然是水包围着山而山脉包围着水的情况。
当然，在需要时，应人工构造流域，以防止集水盆之间相互渗透。
分水岭是山（高原）与水之间的区别，以及湖泊与湖泊之间的距离或湖泊与湖泊之间的联系。
分水岭算法的概念和原理分水岭分割方法是一种基于拓扑理论的数学形态学分割方法。
其基本思想是将图像视为大地拓扑地形。
图像中每个像素的灰度值表示该点的高度。
每个局部最小值及其影响区域称为集水盆地，集水盆地的边界形成一个分水岭。
流域的概念和形成可以通过模拟沉浸过程来说明。
在每个局部最小值的表面上，打一个小孔，然后将整个模型缓慢地浸入水中。
随着沉浸的加深，每个局部最小值的影响区域缓慢向外扩展，在两个流域中，在盆地汇合处筑有水坝以形成分水岭。
分水岭的计算过程是一个迭代标记过程。
L. Vincent提出了更为经典的分水岭计算方法。
在该算法中，分水岭计算分为两个步骤，一个是排序过程，另一个是洪水过程。
首先，将每个像素的灰度级从低到高排序，然后在从低到高的浸入过程中，对h级中的每个局部最小值采用先进先出（FIFO）结构影响域的判断和注释。
分水岭变换获得输入图像的集水盆地图像，集水盆地之间的边界点为分水岭。
显然，分水岭代表了输入图像的最大点。
因此，为了获得图像的边缘信息，通常将梯度图像用作输入图像，即g（x，y）= grad（f（x，y））= {[f（x，y）-f（x-1，y）] 2 [f（x，y）-f（x，y- 1）] 2} 0.5在公式中，f（x，y）代表原始图像，而grad {。
}代表梯度运算。
分水岭算法对弱边缘具有良好的响应。
图像中的噪点和物体表面的细微灰色变化会导致过度分割。
但是同时，应该看到分水岭算法对弱边缘具有良好的响应，并保证获得闭合的连续边缘。
此外，通过分水岭算法获得的封闭收集盆地为分析图像的区域特征提供了可能性。
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clear all
close all
A=imread('12.jpg'); %读入图像
I1=rgb2gray(A); %灰度处理，自动取值二值化
figure;imshow(I1);
level=graythresh(I1);
I2=im2bw(I1,0.3);
figure;imshow(I2);
se = strel('square',1); %进行开运算，使图像形成几个连通域
A2=imerode(I2,se); %降噪处理
figure;imshow(I2);
bw= imopen(I2,se);
figure,imshow(bw); </FONT></P>
<P><FONT color=black> %寻找不包括孔连通域的边缘，并且把每个连通域的边界描出来[B,L] = bwboundaries(bw,4);
figure;imshow(label2rgb(L, @jet, [.5 .5 .5]))
hold on
for k = 1:length(B)
boundary = B{k};
plot(boundary(:,2),boundary(:,1),'w','LineWidth',2)
end
% 找到每个连通域的质心
stats = regionprops(L,'Area','Centroid');
% 循环历遍每个连通域的边界
for k = 1:length(B)
% 获取一条边界上的所有点
boundary = B{k};
% 计算边界周长
delta_sq = diff(boundary).^2;
perimeter = sum(sqrt(sum(delta_sq,2)));
% 获取边界所围面积
area = stats(k).Area;
% 计算匹配度
metric =80*area/perimeter^2;
% 要显示的匹配度字串
metric_string = sprintf('%2.2f',metric);
% 标记出匹配度接近1的连通域
if metric >= 6 && metric <= 7
centroid = stats(k).Centroid;
plot(centroid(1),centroid(2),'ko');</FONT></P>
<P><FONT color=black> % 提取该连通域所对应在二值图像中的矩形区域goalboundary = boundary;
s = min(goalboundary, [], 1);
e = max(goalboundary, [], 1);
%将目标区域分别向两侧延伸7个像素goal = imcrop(A2,[s(2) s(1) e(2)-s(2) e(1)-s(1)]); end
% 显示匹配度字串
text(boundary(1,2)-35,boundary(1,1)+13,...
metric_string,'Color','g',...
'FontSize',14,'FontWeight','bold');
end
goal = ~goal; %将目标区域进行反处理figure,imshow(goal);。