matlab realization, neural network simulation system, the neural network would l...

模式识别和图像处理中特征提取的C++源代码，非常容易集成和使用！-pattern recognition and image processing feature extraction of C source code, and is easy to integrate and use!

高效的图像增强算法，速度快，效果好！欢迎相互交流！-Efficient image enhancement algorithm, fast, good effect! Welcome to exchange!

This toolbox implements the algorithm in a fairly general way in a C file that can be called from Matlab. It allows to perform the traditional NL-means for denoising (for both B&W and color images) but also to use an arbitrary set of patches to perform the denoising. -This toolbox implements the algorithm in a fairly general way in a C file that can be called f rom Matlab. It allows to perform the traditiona l NL-means for denoising (for both B

本程序用VC＋＋实现了BMP图像的均衡化

“冈萨雷斯”《数字图像处理》相关处理代码 VC++ 源代码，对学习数字图象处理很有用，方便修改。-"Gonzalez", "Digital Image Processing" correlation VC source code, learning Digital image processing is used to facilitate change.

基于灰度图像的水平和垂直方向投影，对作图像处理方面的朋友应该有用。-Based on the gray image of the horizontal and vertical projection of the image processing aspects as Friend should be useful.

图像锐化算法，锐化的效果很明显，能达到预期的效果，很适合应用再实践中，运行速度一般。-Image sharpening algorithm, the effect of sharpening it is clear that to achieve the desired results, it is suitable for further practice, the operating speed in general.

多边形常用算法模块 1. 判断多边形是否简单多边形2. 检查多边形顶点的凸凹性 3. 判断多边形是否凸多边形 4. 求多边形面积5. 判断多边形顶点的排列方向，方法一 6. 判断多边形顶点的排列方向，方法二 7. 射线法判断点是否在多边形内8. 判断点是否在凸多边形内-Does the polygon commonly used algorithm module 1. judgements polygons whether simple polygon. 2. inspections polygons apex convex-concave. 3. judgements polygons whether raised- polygon. 4. ask the polygon area. 5. judgements polygons apex the arrangement direction, the method 1. 6. judgements polygons apex arrangement direction, the method 2. 7. beams methods to sentence the break point whether. 8. sentences the break point in the polygon whether in raised- polygon

自适应的编码与解码 在c++环境中可以成功运行-Adaptive encoding and decoding in c++ environment can be run successfully

图像阈值分割是图像理解的关键一步，做好了阈值分割，才能更好的实现图像特征提取和特征匹配。-Image Threshold Segmentation is a key step in image understanding, good threshold segmentation in order to better realize image feature extraction and feature matching.