Cmp_vis_canny

说明：  该代码能够实现K均值聚类算法对彩色图像分割，在MATLAB下实现。(The code can achieve K means clustering algorithm to color image segmentation, in MATLAB to achieve.)

很好的倒频谱计算程序，可立即生成图形，方便读者理解运用。(very good。)

单尺度SSR(Single Scale Retinex)(A Retinex Function)

旁瓣消隐技术在雷达中的应用,包括旁瓣消隐技术的解释(something for slb)

实现人脸识别功能，GUI界面，其中有测试人脸集，识别率95以上(To achieve face recognition function, GUI interface)

介绍了一种典型的ＣＦＡＲ检测算法，使用ｍａｔｌａｂ进行仿真(CFAR detecting algorithm)

此程序采用 FCM，模糊c 均值方法，用于边缘检测(This program uses FCM, fuzzy C mean method, for edge detection)

网格简化， 将复杂的带有很多细节的物体的三维立体网格进行任意比例的简化，使得其减少点和面片的数量并保持物体的基本特征，以达到加快图像显示及压缩文件的效果。(Mesh simplification, the complex three-dimensional grid with many of the details of the object simplified in any proportion, such that it reduce the number of points and surfaces of the sheet and keep the basic characteristics of the object, in order to achieve the speed up of the image display and the effect of the compressed file .)

学习使用OpenCV，对输入的一段彩色视频，用OpenCV实现以下功能或要求: 1. 对输入视频的每一帧图像都用同一个阈值进行二值化； 2.在每帧二值化图像上叠加上含自己学号与姓名等信息的版权字幕； 3. 在处理的过程中，实时显示每帧图片处理之后的效果； 4.将所有这些二值化图像按视频原来顺序合成输出一个视频文件，按原输入视频播放速度的两倍合成； 5. 做成如下的命令行格式，xxx.exe 输入视频文件名 二值化阈值 输出视频文件名（例如 MyBiVideo.exe input.avi 50 output.avi ） 这里的二值化有两种选择，可以手动收入阈值，也可以直接用OTSU算法的较优阈值直接二值化。(Learn to use OpenCV, for some color video input, with the OpenCV following functions or requirements: 1. Each frame of the input video images are binarized using the same threshold value 2. superposed on the binarized image of each frame containing the copyright on the number and the name of their own learning subtitles other information 3. During processing, real-time display after processing each frame 4. All of these binarized image by synthesizing the video output of a video sequence of the original document, the original input composite video playback speed twice 5. made the following command line format, xxx.exe input video file name binary threshold value of the output video file name (eg MyBiVideo.exe input.avi 50 output.avi) Here there are two binary choice, you can manually income thresholds, you can directly use the optimum direct binarization threshold through OTSU algorithm.)

说明：  利用BP神经网络进行图像分割。主要适用于RGB信息丰富的图像。以RGB为BP网络的三个输入，与对应的灰度图对网络进行训练。(The use of BP neural network image segmentation. RGB is mainly applied to information-rich images. BP network to RGB for the three inputs, with grayscale corresponds to the network training.)