encrypt-a-decrypt

hough变换的图像倾斜校正的matlab源码，图像预处理的重要环节之一。(hough transform image tilt correction matlab source, an important part of image pre-processing one.)

一个简单好用的mmn排队算法，其中n=3(a simple and useful mmn method)

汉字识别,可以识别图片中的汉字，进行图像处理，本科毕业设计的资料(Chinese character recognition)

说明：  IQA评估指标包括PLCC，SROCC，KROCC，PSNR，SSIM (Structural Similarity），MSE (Mean Square Error)，RMSE (Root Mean Square Error) ，信息熵 (Information Entropy)算法(IQA evaluation indicators include PLCC, SROCC, KROCC, PSNR, SSIM (Structural Similarity), MSE (Mean Square Error), RMSE (Root Mean Square Error) , Information Entropy (Information Entropy) algorithm)

非常好的椭圆拟合算法，拟合进度很高，算法很好理解，代码质量高(Ellipse fitting algorithm is very good, very fit schedule, a good understanding of algorithms, high code quality)

介绍了DAB 接收机中的OFDM 同步算法，重点对OFDM 接收机方案中基于保护间隔的符号定时估计、频 率偏移估计进行了分析，提出了适用于Eureka147DAB 系统的同步算法；并对各种算法进行了计算机仿真，本文介绍的算法满 足DAB 接收机的要求，有很大的应用价值。(Introduced the DAB the OFDM receiver synchronization algorithms, focusing on OFDM receiver scheme based on the protection of the interval estimation, frequency symbol timing Rate migration estimates are analyzed and some appropriate Eureka147DAB system in the synchronization algorithms And kinds of the computer simulation algorithm, this paper introduces the algorithm of the full The requirements of the foot DAB receiver, a large application value. )

说明：  Harris角点检测，关于角点的应用在图像处理上比较广泛，如图像匹配(FPM特征点匹配)、相机标定等。网上也有很多博客对Harris角点检测原理进行描述，但基本上只是描述了算法流程，而其中相关细节并未作出解释，这里我想对有些地方做出补充说明，正所谓知其然知其所以然，如有不对，还望指正。(Harris corner detection)

图像压缩实例，使用函数wdcbm2()获取信号压缩阀值(the example for image compression using wdcbm2() which is a wavelet function )

包含完整的SVM算法，下载即可使用。其中包括数据集和完整的算法结构，算法结构包括数据清理、核函数升维以及SMO优化算法，可以较好实现数据非线性分类。(Contains the complete SVM algorithm and download it for use. Including the data set and the complete algorithm structure, the algorithm structure includes data cleaning, kernel function upscaling and SMO optimization algorithm, which can better achieve nonlinear data classification.)

将脉冲耦合神经网络PCNN和聚类结合实现灰度图像分割(will PCNN PCNN combining clustering and gray image segmentation)