gspd

说明：  该课题为基于MATLAB的汽车出入库识别系统，带有丰富的人机交互GUI界面。目前毕业设计选题中，传统的中规中矩的车牌识别不易得到高分，必须要在此基础上有所创新方得可以避开其他雷同课题，不会轻易被导师被否决而导致毕设不过。因此建议在车牌识别基础上加入多种方法的对比，看看哪种方法的精度高。虽然目前有很多方法的车牌识别，但是都是在各自的测试库里面测试的，比如测试的车牌图像不同，字符库不同，导致无法做对比。整个设计在一个GUI界面上完成。(This project is based on MATLAB vehicle in and out of the warehouse identification system, with rich human-computer interaction GUI interface. At present, in the topic selection of graduation project, the traditional regular license plate recognition is not easy to get high scores, so it is necessary to innovate on this basis to avoid other similar topics, and it will not be rejected easily by the tutor, leading to the failure of graduation project. Therefore, it is suggested to add a variety of methods on the basis of license plate recognition to see which method has high accuracy. Although there are many methods of license plate recognition, they are tested in their own test library, for example, the test license plate image is different, the character library is different, so it can not be compared. The whole design is completed on a GUI interface.)

包含二值化、canny算子边缘检测、感兴趣区域提取、自动多阈值分割等程序，及分水岭分割和连通域字符识别两篇文章。(Contains two values, canny edge detection, region of interest extraction, automatic threshold segmentation procedures, and watershed segmentation and character recognition two articles connected domains.)

数字图象处理VC++实现,里面有很多图像处理方面的算法，有参考意义。(Digital image processing in VC++)

集成了多种块运动估计算法，对刚接触运动估计算法的同学非常具有参考价值。(Integration of a variety of block motion estimation algorithm for motion estimation algorithm刚接触students have great reference value.)

基于边缘检测的迭代分水岭分割算法源码(内附图片等)(Image Segmentation Using Iterative Watersheding Plus Ridge Detection)

利用turbopixel的超像素图像分割方法，可以显示不同块的颜色。(This is a mex c and matlab code, which uses the turbopixel to segment the object from the image. )

书上的简单DCT图像处理程序，最基本的DCT，简单，价值低(Book on the simple DCT image processing program, the most basic DCT, simple, low value)

说明：  使用硬/软阈值算法，求解各种不同范数约束问题，算法主要有三种(Contains three matrix completion algorithms and a demo script for running them. Also compares against other matrix completion algorithms - Singular Value Thresholding and Fixed Point Iteration.)

CV水平集模型实现对图像的分割，收敛快，收敛效果优于GAC 模型。(CV levelset model to realize image segementation)

这是我自己写的关于 图像处理中retinex、SSR、自适应的对比度增强算法的模板，有很好的效果 希望对你们有帮助( this is for retinex module, I wish it can help for you )