149 C language image processing procedures are complete for each image processin...

通过matlab对多幅图像进行图像分割，并找出关键区域，实现定位-Of multiple images through the matlab image segmentation, and identify critical areas to achieve positioning

VC图像处理系列之一－－图像读写篇 稿件作者：耿　迅 程序名称：ImageTest1 运行环境：Win+VC6.0 注意事项： -VC deal with one of the series of images- images to read and write articles Manuscripts Authors: Geng Xun Name: ImageTest1 operating environment: Win+ VC6.0 NOTES:

通过分类器自动识别图像中的人脸-Automatic recognition through classifier human face images

用于BF533处理器的Ycbcr与RGB的转换。-BF533 processor for YCbCr and RGB conversion.

采用log算法对图像进行边缘检测并附图说明。

这是我前一段时间收集的一个关于图像处理的代码，真可谓是丰富多彩。一定会您有用。里面涉及各种关于图像处理的源代码。-this is a magic image processing sourc code, whic i got the other day. it must be useful for people who research image compression

本文提出了一种新的跨国家的障碍 检测技术为基础的立体视觉系统。 原始图像的预处理的高斯 过滤器和对比度限制的自适应直方图 均衡（ CLAHE ）方法来削弱作用 噪音，光线和对比度。哈里斯的角落位于与子像素精确。 -Cross-country intelligent vehicles always work in complicated environments with varying illuminations. The paper presents a new cross-country obstacle detection technology based on stereo vision system. The original images are preprocessed by Gaussian filter and contrast-limited adaptive histogram equalization (CLAHE) method to weaken the effect of noise, light and contrast. Harris corners are located with sub-pixel accurate. To guarantee the overall system real-time performance, feature-based matching techniques are studied and fundamental matrix is calculated based on random sample consensus (RANSAC). Also restrains are studied to eliminate pseudo matching pairs. Then data interpolation is introduced to build elevation maps. Edge extraction and morphological processing are concerned to accomplish obstacle detection. Experiment result

很实用的C#图像处理边缘检测代码，包括使用sobel/priwit等算子-Very practical C# Image processing edge detection code, including the use sobel/priwit operator, etc.

基于directshow车型识别程序c++代码，可根据车型的图像特征自动识别车型。-DirectShow-based model identification procedures c++ Code, according to models of automatic identification of image feature models.

本系统实现的是完成多光谱的tm图象与spot全色图象的融合处理,最终得到的是一幅新图象. 主要的操作主要是多光谱的tm图象的导入,spot全色图象的导入,多光谱的tm图象stop全色图象的显示,融合算法的选择处理,融合结果图象的显示