OtsImageCtl.java

基于神经网络的地面裂缝检测软件，可以在界面上选择各种功能去检测。(Ground crack detection software based on Neural Network)

本案例采用基于块匹配的图像拼接流程来执行拼接操作，载入图片文件夹来作为待拼接对象，通过进行图片序列的匹配、融合来得到拼接效果，并分别对灰度图像、彩色图像进行处理。(This case is based on block matching process to perform image stitching splicing operation, load images folder as an object to be spliced, by matching the fusion image sequence to get the mosaic effect, respectively, on the gray image, color image processing .)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

face recognition example for learning

Lung Cancer Detection Using Image Processing Techniques

光流法的程序，利用传统光流法思想，亲测有效，效果不错(Optical flow method program, pro-test, good results)

MATLAB程序-按物理光学模型生成PSF(MATLAB program - generating PSF by physical optics model)

基于JPEG压缩的无参考图像质量评价算法，输入一幅图像，输出图像的评价值，值在0-100之间，越接近0图像的质量越好(JPEG-based compression algorithm for no-reference image quality assessment, an input image, the output image uation value, a value between 0-100, closer to 0 the better the image quality)

波包生成函数，适用于初学者对小波的理解，很实用(Wave packet generation function, for beginners to understand the wavelet, it is practical)

基于图和流形排名的图像显著性检测算法，MATLAB实现(Manifold ranking based on maps and image saliency detection algorithm, MATLAB realization)