learned线段检测算法

learned线段检测算法
英文回答：
Learned Line Segment Detector (LSD)。

The Learned Line Segment Detector (LSD) is a line segment detection algorithm that uses a machine learning approach to detect straight lines in images. It was developed by Rafael Grompone von Gioi, Jérémie Jakubowicz, Jean Michel Morel, and Gregory Randall in 2012.
LSD is based on the idea that line segments can be characterized by their local image properties. The
algorithm first computes a set of local features for each pixel in the image. These features include the pixel's intensity, gradient, and curvature.
The algorithm then uses a machine learning classifier
to learn a function that maps these local features to the probability of a pixel being on a line segment. The
classifier is trained on a dataset of images that have been manually annotated with line segments.
Once the classifier has been trained, it is applied to the input image to produce a probability map. The probability map indicates the likelihood of each pixel being on a line segment.
The final step of the algorithm is to extract line segments from the probability map. This is done by thresholding the probability map and then connecting the resulting connected components.
LSD is a fast and accurate line segment detection algorithm. It can be used to detect line segments in a variety of images, including natural images, man-made images, and medical images.
Applications of LSD.
LSD has a wide range of applications, including:
Object recognition.
Image segmentation.
Medical imaging.
Remote sensing.
Industrial inspection.
Advantages of LSD.
Fast and accurate.
Can detect line segments in a variety of images. Easy to use.
Disadvantages of LSD.
Can be sensitive to noise.
Can miss line segments that are not well-defined.
中文回答：
学习型线段检测算法 (LSD)。

学习型线段检测算法 (LSD) 是一种线段检测算法，它使用机器
学习方法来检测图像中的直线。

该算法由 Rafael Grompone von Gioi、Jérémie Jakubowicz、Jean Michel Morel 和 Gregory Randall 于 2012 年开发。

LSD 基于这样的思想，线段可以用它们的局部图像属性来表征。

该算法首先为图像中的每个像素计算一组局部特征。

这些特征包括
像素的强度、梯度和曲率。

然后，该算法使用机器学习分类器来学习一个函数，该函数将
这些局部特征映射到像素在线段上的概率。

该分类器在已使用线段
手动注释的图像数据集上训练。

一旦训练了分类器，它就会应用到输入图像以生成概率图。

概
率图指示每个像素在线段上的可能性。

该算法的最后一步是从概率图中提取线段。

这是通过对概率图进行阈值处理，然后连接由此产生的连通分量来完成的。

LSD 是一种快速而准确的线段检测算法。

它可以用来检测各种图像中的线段，包括自然图像、人造图像和医学图像。

LSD 的应用。

LSD 具有广泛的应用，包括：
目标识别。

图像分割。

医学成像。

遥感。

工业检测。

LSD 的优点。

快速而准确。

可以检测各种图像中的线段。

使用方便。

LSD 的缺点。

可能对噪声敏感。

可能错过定义不佳的线段。