另一个用C++读取 jpg的实例程序，非常实用，仅供参考

purpose computes histogram and some statistical measures (min, max, ...) for a list of values (one per line) compile gcc -g -o analyze_values analyze_values.c -lm -purpose computes histogram and some stati stical measures (min, max, ...) for a list of values (one per line) compile g cc-g-o analyze_values analyze_values.c- lm

YUV与RGB互转动态链接库 可直接使用 -YUV and RGB referrals dynamic link library can be used directly

运用matlab的形态学，把一幅图片的豆子数目数出来的程序，自己编的，希望和大家分享！-Morphology using matlab to a number of pictures a few beans out of the procedure, its own series, and would like to share!

The aim of Optical Character Recognition (OCR) is to classify optical patterns (often contained in a digital image) corresponding to alphanumeric or other characters. The process of OCR involves several steps including segmentation, feature extraction, and classification. This program use Image Processing Toolbox to get it. For more information, visit: http://www.matpic.com

读取3dmax生成的dxf三维模型，在视窗内显示三个视图的效果。-3dmax read dxf generated three-dimensional model, in the view window shows the three effects.

抗任意角度旋转的图像匹配算法的matlab实现-image matching of any rotation

将对话框“钉”在屏幕上-dialog box will "nail" on the screen

经典的基于PCA面部识别系统，含注释及测试图片-Classical PCA-based facial recognition system, including the Notes and the test image

本程序可以实现画圆,直线,bezier曲线,矩形等图形,并且是用鼠标操作的,同时也可以实现图形的任意倍的放大,缩小,平移和清屏,退出功能.-this procedure can be achieved Circle, Line, bezier curves, rectangles and other graphics, and the mouse is used to operate, but also the realization of graphics arbitrary times magnification, narrow, and the screen translation, from functional.

基于神经网络的文字识别系统 本目录主要包括：文档和两个源代 其中源代码是识别程序的，另一个是矩阵类库的。已经保存了训练好的网络权值，所以第一次使用识别程序时，可以直接运行Release目录下的可执行文件，然后对图片目录中的测试图片进行读入、识别。当然也可以自行用训练样本训练网络，不过要注意训练样本的选择，否则可能识别率很低。训练样本选择的原则是，尽可能的有代表性，在训练时间不至于太长的情况下训练样本数目尽量多。-Based on neural network character recognition system catalog include: the two source documents and source code generation which is to identify the procedure, and the other is the matrix class library. Has been preserved trained network weights, so the identification procedures used for the first time, you can directly run the Release directory of the executable file, and then on the picture of the test directory to read into the picture, identification. Of course, we can use training samples to train the network, but attention should be paid to training samples, otherwise it may be very low recognition rate. Training sample selection principle is that, as far as possible have representation in the training time not too long a number of cases as many as possible training samples