Contourlet

光流法实时实现的文献及代码，2012发表于cvpr，200*200的图像，每秒可达200帧，2012_CVPR_Lip-motion events analysis and lip segmentation using optical flow(Optical flow method to achieve real-time literature and code, 2012 published in cvpr, 200* 200 images per second, up to 200, 2012_CVPR_Lip-motion events analysis and lip segmentation using optical flow)

图像去雾基于暗原色先验去雾，何凯明算法的源代码改进，(Dark colors on the image to fog prior to fog, He Kaiming algorithm source code improvements,)

用Visual C编的用于语音的频频谱的检测，能显示出来语音的频谱图。 (Visual C series of the spectrum for voice detection, displayed the frequency spectrum of the voice.)

本代码实现了基于肤色的人脸分割程序，代码采用Matlab编写，包含了四个测试样例和结果分析。(This is matlab code about face detection based on face color.)

C# 使用Halcon进行模板匹配定位(C# uses Halcon for template matching and location)

数​ 字​ 图​ 像​ 处​ 理​ 中​ 的​ b​ p​ m​ 图​ 像​ 读​ 取(Digital image processing of the image b p m reading)

高效的文章分句算法程序,将由标点符号分开的语句的起始位置和结束位置记录到结构体里()

本程序用于对工件图像的预处理，边缘提取等。将改进遗传算法和Hausdorff距离结合用于工件识别。采用canny边缘为匹配特征，将修正的Hausdorff距离作为相似性度量准则，并应用遗传算法进行最佳匹配的快速搜索，成功实现了目标物体的匹配识别(This procedure used for the workpiece image preprocessing, edge extraction and so on. Will improve the genetic algorithm and Hausdorff distance combination for workpiece identification. Using canny edge for matching characteristics, will be amended Hausdorff distance as similarity measurement criteria and the application of genetic algorithm is the best match of the Quick Search, the successful achievement of the target object matching identification)

说明：  hog 特征 基于matlab的 RGB提取(realize the hog feature)

Gray Level Edge Thinning Method Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.