watershed3

碰撞检测完整实例 (Complete example of collision detection)

is very good,i think you will be liake it

求解l1范式的值，用于压缩感知中的稀疏表示。进行分类(Solving the value of l1 paradigm for compressed sensing of sparse representation. Classification)

HOG LBP 在python matlab C++环境下的实现(Implementation of HOG LBP in Python matlab C++ environment)

计算进口边界条件为超音和亚音条件下，气流流经凸包时的二维流动状况(program for calculate air flows through the convex hullto in the import boundary conditions of supernic and subsonic)

利用相位相关法实现了图像的匹配，这种方法的优点是提取速度快，方法简单，运算量少。(Using the phase correlation method to realize the image matching, the advantage of this method is the extraction method is simple, fast, less computation.)

包含滤波模板，形态学运算，边缘检测结合经自己修改过的hough变换编写的vc程序，成功检测机场跑道和任何图像中最明显的现状特征，经测试，检测精度高。对学习vc编程用于图像处理有帮助。(hough transform based image processing package which is useful for detecting airfield like straight line features.)

说明：  相当的经典啊 是基于matlab的 大家做图像匹配的都可以用的到,做三维重建方面的。(Rather is based on the classic ah matlab we do the image matching can be used for that, so three-dimensional reconstruction.)

说明：  一、主要研究内容 1.基本内容 本设计目标在于利用Matlab强大的图像处理能力和实用便捷的编程方法，通过处理包含人脸的视频帧系列图像，灰度积分投影技术的眼睛定位方法，进而利用perclos计数，计算眨眼率，从而得到比较准确的疲劳状况。包括lun文初稿撰写。 2.具体要求 本设计基于灰度积分投影技术的眼睛定位方法，再结合perclos技术。首先通过图像预处理技术得到灰度分配较为均匀的图像,然后分别利用水平和垂直灰度积分投影曲线结合人脸的结构特征找到眼睛的位置坐标,实现了准确的眼睛定位,通过perclos技术技术眨眼率，根据先验值得到是否疲劳。 二、算法原理 视频输入——预处理去除非人脸区域——人脸定位——人眼定位（灰度积分投影）——眼睛张合度——perclos技术统计——输出结果 三、GUI界面设计 [需要有一定编程功底](1. Basic contents The goal of this design is to use the powerful image processing ability of MATLAB and the practical and convenient programming method, through processing the video frame series images including face, the eye location method of gray integral projection technology, and then using PERCLOS count to calculate the blink rate, so as to get a more accurate fatigue condition. Including the first draft of Lun.)

图像处理.最全的压缩编码与解码.非常值得学习(Image processing most complete compression encoding and decoding. Worth learning)