DPC

NLMS算法的仿真，用于对比LMS算法，描绘了平方误差和输出图形(The simulation of NLMS)

《数字图像处理（第三版）》课后习题答案，作者冈萨雷斯(Answers to Exercises after Class of Digital Image Processing (Third Edition),author Gonzalez)

图像中数字水印matlab编码，水印的嵌入提取及嵌入强度(Digital watermark image matlab coding, the embedded watermark extraction and embedding strength)

说明：  一、课题介绍 本设计为基于MATLAB的火焰烟雾火灾检测系统。传统的采用颜色的方法，误识别大，局限性强。结合火焰是实时动态跳跃的，采用面积增长率，角点和圆形度三个维度相结合的方式判断是否有火焰。该设计测试对象为视频，通过下一帧和上一帧的差异发现是否有火情，并可发出语音报警。本设计带有一个人机交互式GUI界面，界面友好。是个不错的bishe选题。 二、算法流程 结合火焰的面积增长率，角点和圆形度三个维度综合判断。并且得出每帧图像火焰部分的该三个参数，实时显示在GUI上。 三、GUI界面设计(This design is based on MATLAB flame smoke fire detection system. The traditional method of using color has large error recognition and strong limitation. Considering that the flame is real-time and dynamic jumping, the area growth rate, corner and roundness are combined to determine whether there is flame. The test object of the design is video. Through the difference between the next frame and the previous frame, whether there is fire is found and the voice alarm can be sent out. This design has a personal computer interactive GUI interface, the interface is friendly. It's a good choice for BiShe.)

采用了Harrtraining和离子滤波算法实现了拥挤人群人头计数，非常有用。VC++和Opencv开发，采用Oepncv中的Harrtraining训练一个分类器即可运行(Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. We integrate human detection and tracking into a single framework, and in- troduce a conrmation-by-classication method to estimate condence in a tracked trajectory, track humans through occlusions, and eliminate false positive detections.)

说明：  运用MATLAB，软件结合模板匹配原理进行的英文字符识别系统(English character recognition system based on MATLAB and template matching)

基于相位一致性与K-means方法的结合边缘检测(PC and K-means)

经典的跟踪算法，可以对人脸进行实时的跟踪。(Classical tracking algorithm can be real-time face tracking.)

meanshift 图像分割及平滑 包括meanshift的论文及ppt(Code for the Edge Detection and Image Segmentation system and the paper)

　对经典的二值化方法Ostu 算法和Bernsen 算法中存在的缺点进行了分析, 提出一种结合Canny 算子的图像 二值化方法.该方法综合考虑了边缘信息和灰度信息, 通过边缘附近种子点在高阈值二值化图像中的填充和低阈值 图像对它的修补而得到二值化结果图像, 较好地解决了经典二值化方法中存在的抗噪能力差、边缘粗糙、伪影现象 等缺点.实验结果证明, 该方法能够较好地解决低对比度图像和目标像素灰度不均匀图像的二值化问题(The disadvantage of the classical binary method Ostu Bernsen algorithm and algorithms exist were analyzed, one binding Canny operator image binarization method. This method considers the edge information and gray information, through seed near the edge point padding and a low threshold image to its repair in a high threshold binary image to obtain a binary result image, it solves the noise immunity classical binary method exists difference, rough edges, artifacts phenomenon and other shortcomings. the experimental results show that this method can solve the low-contrast image and the target image pixel gray uneven binary problem)