8位/24位图像的腐蚀膨胀算法。适合图像处理的初学者学习。

本程序用VC＋＋实现了BMP图像的均衡化

绘出图像中主要线路的走向 laneMaking-Mapped images to the main lines laneMaking

伪Zernike矩特征提取，Zernike矩特征提取，供参考，很有用-Pseudo-Zernike moment feature extraction, Zernike moment feature extraction, for reference, very useful

（1）应用9×9的窗口对上述图象进行随机抽样，共抽样200块子图象； （2）将所有子图象按列相接变成一个81维的行向量； （3）对所有200个行向量进行KL变换，求出其对应的协方差矩阵的特征向量和特征值，按降序排列特征值以及所对应的特征向量； （4）选择前40个最大特征值所对应的特征向量作为主元，将原图象块向这40个特征向量上投影，所获得的投影系数就是这个子块的特征向量。 （5）求出所有子块的特征向量。 -(1) the application of 9 × 9 window of these images at random, a total sample of 200 sub-image (2) all sub-images according to out-phase into a 81-dimensional row vector (3) all 200 lines for KL transform vector, derived its corresponding covariance matrix of eigenvectors and eigenvalues, in descending order by eigenvalue and the corresponding eigenvector (4) a choice to 40 corresponding to the largest eigenvalue eigenvector as the PCA, the original image block to the 40 feature vectors on the projection, the projection coefficients obtained by this sub-block eigenvector. (5) calculated for all sub-block eigenvector.

在VC6.0中的一些基本操作,常常用来进行简单的学习和常规的练习 -in VC6.0 of some of the basic operations, often used for the study and simple conventional exercise

利用vc++对动态目标进行检测，也可配合摄像头使用-Using vc++ for dynamic detection of targets can also be used with the camera

关于图象处理的一个开发包,希望对大家有帮助-image processing on a development kits, we hope to help

此程序通过遗传算法(ga )实现灰度图像的分割,遗传算法的计算过程首先是将实际的优化问题编码成符合串,-This procedure through the genetic algorithm (ga) realize grayscale image segmentation, genetic algorithm calculation process is to first of all, the actual coding optimization problem into line with the string,

Watershed algorithm.图像分割的分水岭算法的源程序。-Watershed algorithm. The watershed image segmentation algorithm of the source.

30个图像处理的VC++ 源代码，包括256色转灰度图,Hough变换,image_j1,PCA,Walsh变换,对比度拉伸,二值化变换,反色, 方块编码,傅立叶变换,高斯平滑,灰度均衡,均值滤波,拉普拉斯锐化（边缘检测）, 离散余弦变换,亮度增减,逆滤波处理,取对数,取指数,梯度锐化,图象处理,图像镜像, 图像平移,图像缩放,图像细化,图像旋转,维纳滤波处理,用Canny算子提取边缘,阈值变换,直方图均衡.-30 image processing VC++ Source code, including 256 colors to grayscale, Hough transform, image_j1, PCA, Walsh transform, contrast stretching, binarization transformation, anti-color, box encoding, Fourier Transform , Gaussian smoothing, gray balance, mean filter, Laplacian sharpening (edge detection), discrete cosine transform, the brightness increases and decreases in inverse filtering deal, check on the number of check index, the gradient sharpening, image processing, mirror image, image translation, image scaling, image thinning, image rotation, Wiener filtering treatment using Canny edge extraction operator, threshold transform, histogram equalization.