Criminisi

说明：  非常详细的一篇论文，仔细介绍了手指静脉识别的的全过程(A very detailed paper, carefully introduced the finger vein identification process)

MC算法实现CT医学图像的三维重建，面绘制技术(MC algorithm CT medical image reconstruction, surface rendering technology)

基于图像检索的matlab代码，基于内容的图像检索中的一些关键环节：特征提取：颜色直方图；纹理特征等 相似度：马氏距离，欧氏距离等 相关反馈：机器学习方法，如SVM，神经网络等 检索与分类：两个很相似的样本距离很小，虽然两个不相似的样本距离未必很大(content-based image retrieval of some of the key issues : Feature Extraction : color histogram Texture characteristics of similarity : Mahalanobis distance, the Euclidean distance relevance feedback : machine learning methods, such as SVM. Neural network search and classification : two very similar samples from the small, although the two are similar to the samples may not be much distance)

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.)

本工程在C6678上实现了BMP图像的读取，滤波，锐化等操作。可以作为多核DSP图像处理的资料，自己在CCS6平台上测试验证没有问题(This project has realized the reading, filtering and sharpening of the BMP image on C6678. It can be used as a multi-core DSP image processing data, and to test validation on the CCS6 platform)

分割点云，并通过局部拟合求取法向量，实现点云压缩(Split point cloud, and through local fitting strike normal vector of point cloud compression)

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)

基于图割方法的图像分割程序代码，希望对您有帮助哦！(graph cut method to segment images, it is nessary for you to have a look if you are doing image segmentation.)

压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为SP算法，对256*256的lena图处理，比较原图和SP算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间(Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix and SP algorithm as the reconstruction algorithm. Compare lena figure and the reconstruction results using SP algorithm at different sampling ratio (0.74,0.50.3),then each runs 50 times, compare the performance of PSNR and each running time)

以图像拼接目标为应用背景，对图像处理配准和融合的基本原理及相关算法进行研究；利用matlab对相关配准和融合算法进行实现并优化;并将配准和融合算法应用于图像拼接中（给定某个真实场景的一组局部图像，然后对这一组图像进行拼接，最终形成一个图像拼接系统）。要求配准和融合能单独进行工作，形成独立的程序(The basic principles and algorithms of image registration and fusion are studied with the image stitching target as the application background. MATLAB is used to implement and optimize the related registration and fusion algorithms, and the registration and fusion algorithms are applied to the image mosaics (given a set of local images of a real scene, and then to this group) The image is stitching to form an image mosaic system. Registration and fusion are required to work independently and form separate programs.)