demo

利用visualC++和图像处理的知识，编写程序对果蔬进行自动识别(Using visualC++ and image processing knowledge, write a program for automatic identification of fruits and vegetables)

本程序可实现维纳滤波，可应用于反褶积等反问题的求解过程中，是非常简单实用的(This program can be realized Wiener filter can be applied to deconvolution inverse problems and the process is very simple and practical)

天津工业大学课程设计，内容包含vs2010对图像的灰度化，二值化，边缘检测。包含单纯c语言编写的对图像的灰度化，二值化，边缘检测的一个.C文件，可以直接用vc6.0运行，也可以直接在DSP上运行，还包含一份详细的设计报告。(Tianjin Polytechnic University curriculum design, content includes vs2010 grayscale image binarization, edge detection. Contains pure c language for image graying, binarization, edge detection is one. C file that can be run with vc6.0 can also be run directly on a DSP, also contains a detailed design report.)

用VC编写的一个图像处理的程序：它可以实现图像的增强，包括：图像的平滑、中值滤波、梯度锐化、拉普拉斯锐化和伪彩色编码(VC prepared by an image processing procedures : it can enhance the images, including : image smoothing, Median filtering, sharpening gradient, Laplacian sharpening and pseudo-color coding)

图像处理的KMP算法源程序，KMP算法是一种基本的、实用的字符串比较算法，广泛应用于图像处理和模式识别。(Image processing algorithms source KMP, KMP algorithm is a basic, practical string comparison algorithm, widely used in image processing and pattern recognition.)

gabor滤波，优点是分析周围的像素点，是一种物质的可能性大。(gabor filter, the advantage of pixel analysis surrounding the possibility of a substance is large.)

说明：  最二小乘影像匹配，精度可以达到0.01个像素，也可以最二小乘影像模板匹配。经过修改后可以直接用，只要调用一个函数就搞定，函数参数的说明很清楚，绝对不会有任何困难，非常好用。(Most two Theravada image matching accuracy can reach 0.01 pixel images can also be the most two Theravada template matching. After modifications can be directly used, as long as is you call a function, function parameters, the description is clear and will not have any difficulties, very easy to use.)

VC++图像平滑处理+程序源码，实现图象的平滑（去噪声），锐化功能，测试时请在C盘下放一个测试用的Bmp图片，路径：C: est.bmp，没有的话没法测试。如上图所示是水平平滑处理，可以对比下，不过感觉颜色失真了，有兴趣的看一下。命令行编译过程如下： 　　vcvars32 　　rc bmp.rc 　　cl smooth.c bmp.res user32.lib gdi32.lib(VC++ image smoothing+ program source code, to achieve a smooth image (to noise), sharpening function in the C drive when testing a test of decentralization Bmp picture, path: C: test.bmp, no words can not test . Is shown above the level of smoothing, you can compare the next, but the feeling of color distortion, interested look. Command-line compiler as follows: vcvars32 rc bmp.rc cl smooth.c bmp.res user32.lib gdi32.lib)

物理光学法+物理绕射计算远场RCS的程序代码，c++程序(Physical optics+ physicaldiffraction computing far-field RCS program code, c++ program)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)