指纹识别源代码 - finger

亚像素位移和变形梯度测量采用数字图像/散斑相关(Subpixel displacement and deformation gradient measurement using digital image/speckle correlation(„ DISC… ))

说明：  KFCM聚类算法进行图像分割，分割效果好(KFCM clustering algorithm for image segmentation, segmentation effect is good)

本程序是用似然比检验的方法进行profile中的变点检测(This procedure is used likelihood ratio test method of change point detection profile)

用小波域隐马尔科夫树模型进行图像降噪的matlab软件，rice大学编制(Software For Image Denoising Using Wavelet-Domain Hidden Markov Tree Models)

提取糖尿病视网膜病变眼底图像上硬性渗出。将彩色图像转为灰度图，对灰度图进行形态学处理、去背景、阈值分割，最终将原图上的硬性渗出区域用绿色标记出来。(this word is to extrac the hard exudates on diabetic retinopathy fundus image. The color image to grayscale on grayscale morphological processing to the background, threshold segmentation, ultimately on the original hard exudates area marked in green.)

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)

简单图像颜色特征提取，用于自己使用，基本常规的那种(Simple Image Color Feature Extraction)

掌纹图像双峰法二值化，边界跟踪提取掌纹轮廓线，harris角点，手动提取关键点建立坐标系和画正方形(Palmprint image bimodal binary, boundary tracking extract palmprint contour, harris angle manually extract key point to establish a coordinate system and draw a square)

基于Hough变换的虹膜自动分割的matlab代码(Automatically based on Hough transform in iris segmentation matlab code)

利用matlab，对图像进行高斯滤波，然后通过非极大值抑制，设置双阈值，实现图像边缘检测(Image edge detection)