Common-standard-pics

这个是图像处理中的hough变换的C++源代码，工需要的同学参考学习。(This is the image processing hough transform C++ source code, engineering students need to learn.)

图像分割处理的小波变换算法源代码，使用vc++(Wavelet transform image segmentation algorithm source code vc++)

AutoCAD二次开发的图像处理代码,对彩色图像进行区域生长,然后提取边界,实现图像分割.(AutoCAD second development of image processing code, color images of regional growth, and then extract the boundary, realize image segmentation.)

通过数字图像相关的方法计算两幅图像之间的位移，计算时间较长，是最基础的DIC，没有优化。(Digital image correlation method to calculate the displacement between the two images, the time is longer, is the most basic DIC, no optimization.)

本压缩包有canny算子的源程序代码和测试图片。(The archive has canny operator of the source code and test images.)

基于肤色的图像分割，是用matlab实现的，希望大家有用(Image segmentation based on skin color is achieved with matlab, I hope it would be useful)

图象处理用于对BMP格式的图象进行几何校正.(image processing used to BMP format images geometric correction.)

huffman编码 基于对BMP格式图像的编码！ 具体你们自己看看！(Huffman code)

数字图像处理第二版英文版（冈萨雷斯）.pdf(Digital Image Processing Second Edition English (Gonzalez). Pdf)

：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相结合的方法对叶片多特征进行特征降维，将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量 机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)