对图像进行边缘提取，采用canny算子提取边缘

指纹图像的增强,细化.指纹特征点的提取,单个特征点的对比,单个特征星的对比,指纹图像的对比-fingerprint image enhancement and refinement. Fingerprint Feature Extraction Point, a single point of contrast, Characteristics of single-contrast images of fingerprints

几何活动轮廓模型（snake模型）中level-set算法的matlab源码-Geometric active contour model (snake model) in the level-set algorithm matlab source

一些关于图像阈值确定的matlab程序，包括迭代阈值，最小类内方差，最大熵，和用matlab库函数对图像进行边缘检测。可运行-Number of image thresholding matlab identified procedures, including iterative threshold, the smallest category of variance, maximum entropy, and the use of matlab library function of the image edge detection. Run

dicom的转换程序，可转成bmp，jpg，pnm等，一群德国牛人写的，超强-DICOM conversion procedures, could be converted into bmp, jpg, pnm, etc., a group of cattle were written in Germany, super-

转动箱子的动画,多维旋转图象,可以多角度观察,利用SIN函数-rotating box animation, multi-dimensional rotating images, more angle, the use of SIN function

仿射变换法求深度信息，目前最好的方法 function [Z,D11,D12,D22] = diffusion_kernel_function(gx,gy,im) gx,gy 为x,y方向偏导数 Z 为恢复出来的是深度信息。 函数适应于从 图像法相信息恢复高度信息-Affine transformation method the depth of information, is currently the best way to function [Z, D11, D12, D22] = diffusion_kernel_function (gx, gy, im) gx, gy for x, y direction of the partial derivative of Z is out to restore the depth of information. Function adapted from the image information to resume a high degree of information law

用Efros和Freeman的纹理合成算法,利用误差最小的边界剪切法进行纹理图片的合成-By Efros and Freeman

本代码是关于图像纹理识别方法，提供几何运算、正交运算、边缘轮廓、图像分析等功能，适合广大图像处理者使用-The code is on the image texture recognition method, providing geometric calculations, orthogonal computing, edge contour, image analysis and other functions, for the vast numbers of image processing to use

图像处理中，可以显示图像，并对图像进行操作处理，形态变换等，是图形图像处理有用的一个程序-image processing, can show images and image processing operation, morphological transformation. Graphic Image processing is a useful procedure

AdaBoost的Matlab程序，非常通俗易懂，适合初学者学习AdaBoost的运算流程-AdaBoost the Matlab program, very user-friendly, suitable for beginners to learn computing AdaBoost flow