5.2

说明：  基于c#运动控制及图像处理项目源码，有兴趣可以看看(Based on C# motion control and image processing project source code)

采用分水岭算法对图像进行分割。直接对图像进行分水岭算法，效果并不理想。本方法使用形态学重建技术对前景对象进行标记，求局部极大值，最终将分割好的图像进行伪彩色显示，让结果更加明显。适用于较复杂的图像分割处理。(Using watershed algorithm for image segmentation. Watershed algorithm for image directly, the effect is not ideal. This method uses morphological reconstruction technique foreground object is marked, find local maxima, eventually dividing good pseudo-color image display, make the results more apparent. Applicable to more complex image segmentation processing.)

radon算法opencv实现，能够很好的实现图像的水平旋转矫正。( implementing the radon by opencv.)

林健写的Matlab在图像处理与目标识别方面的应用实验，包括染色体识别与统计、汽车牌照定位与字符识别、基于BP神经网络识别字符的简单实验。 (Lam Kin Writing at the Matlab image processing and target recognition application experiments, including chromosome identification and statistics, vehicle license positioning and character recognition, based on BP neural network easy to identify characters in the experiment.)

用vibe算法提取动态背景的前景信息，背景为白色(Vibe algorithm is used to extract foreground information of the dynamic background, the background is white)

视网膜血管检测的Gabor变换和机器学习，教程 本教程将演示如何Gabor变换和广义 的线性模型（GLM）可用于视网膜血管检测 图像。 ，我们将尝试检测视网膜血管从 的训练图像，首先，Gabor滤波器与图像卷积。 GLM将使用Gabor变换的图像特征确定 （独立变量）和容器的位置 为结果（因变量）。( Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial This tutorial will demonstrate how Gabor transforms and generalized linear model (GLM) can be used for detection of retinal vessels in images. Specifically, we will attempt to detect the retinal vessels a training image , by first, convoluting multiple Gabor filters with the image. A GLM will be determined using the Gabor transformed images as features (the independent variables), and the locations of the vessels as the outcome (the dependent variable).)

LDA 的matlab源码实现，Jonathan Huang编写的，是目前唯一可用于且正确的源码，可用于图像特征降维(LDA to achieve the matlab source, Jonathan Huang, prepared, is the only can be used and the correct source, can be used for image feature dimensionality reduction)

利用霍夫线检测实现车道线的自动检测并判断是否偏离(Using Hof line detection to achieve automatic detection of lane line and determine whether or not to deviate the)

本程序能够综合地实现图像边缘细化，而且程序够复杂。(This procedure can be integrated to achieve the Image Edge thinning, and the procedures complex enough.)

System Generator中伪彩色增强建模(Pseudocolor enhancement model in the System Generator)