huoquzhidingyanse

说明：  分块直方图均衡化处理图像 用户输入分块的x,y方向的分块个数，即可将图形分成各个小块进行直方图均衡化。 大津法处理图形，包括一维大津法和二维大津法的实现 (the realization of the Histogram equalization algorithm. the realization of otsu algorithm to process the images)

对图像进行旋转和缩放的源代码,支持原图像的抽样处理及任意角度的旋转(The image rotation and scaling in any direction)

几个大牛对集成了国内外特征提取最前沿的算法，特征提取，DOG,HARRIS,HARRIS-LAPLACE,HARRIS-AFFINE,MSER.描述符，SIFT,AFFINE-SIFT,GLOH.经测试，速度快，描述符准确。(Integration of feature extraction algorithms from several expert of domestic and international, feature extraction： DOG, HARRIS, HARRIS-LAPLACE, HARRIS-AFFINE, MSER； Descriptors： SIFT, AFFINE-SIFT, GLOH. The test reveal the speed and accurate descriptor.)

说明：  基于LBP纹理特征的运动目标检测算法.rar(Moving target detection algorithm based on LBP texture features. Rar)

图像算法开放库，对图像处理的，希望对学习者有所帮助！(Image algorithm open library of image processing, and they hope to help learners!)

基于Visual C++的图像边缘检测工程，以Canny为例(Visual C++-based image edge detection works to Canny Case)

说明：  实现机器视觉双目标定，三维重建等算法，具有很好地擦考价值( Robot with two cameras to switch recognition system. (Note that not binocular vision) and the reference used opencv1.0 cmv. )

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

图像的几何变换，基于VC++的MFC的。旋转、放大、缩小等(Image geometric transformation, based on the VC++ the MFC. Rotate, zoom in, zoom out, etc.)

使用K近邻算法对一个2维德样本集进行分类，样本集的分布为混合高斯分布。(K nearest neighbor to use a 2 Verde sample set for classification, the distribution of sample set for mixed Gaussian distribution.)