blindwatermark

运动目标检测一系列文章，包含很多新的算法，可以参考研究一下(Moving target detection range of articles, includes many new algorithms, you can refer to study)

C#+EmguCV机器视觉开发平台，功能：基本的图像处理工具、随意配置执行流程、二维码识别、文字识别等等。(C+EmguCV machine vision development platform, functions: basic image processing tools, arbitrary configuration of the execution process, two-dimensional code recognition, character recognition and so on.)

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)

鼠标移动到哪里 就显示那里的颜色像素值

基于肤色分割和SVM的人脸检测的MATLAB 代码，主要是利用YCgCr来来进行肤色建模，然后结合SVM进行检测。 希望对您有所帮助！(Based on skin color segmentation and SVM Face Detection MATLAB code, mainly used to carry out color YCgCr to model, and then tested with SVM. Want to help you!)

目的是改善影像质量，包括去除高频噪声与干扰，及影像边缘增强、线性增强以及去模糊等。分为低通滤波（平滑化）、高通滤波（锐化）和带通滤波。(The purpose is to improve the image quality, including the removal of high frequency noise and interference, and image edge enhancement, linear enhancement and deblurring. Into a low-pass filter (smoothing), high-pass filtering (sharpening) and bandpass filtering.)

C#实现多边形颜色的填充，主要是种子填充和种子扫描线填充两种算法。(C# implementation of the polygon fill color, mainly seeds and seed filling scan line fill two algorithms.)

使用sift+RANSAC完成两幅图像的特征提取和匹配，并将较小图像区域在另一幅中用方框圈出来。运行plot.m。(This code uses sift and RANSAC to extract features of two images and then finds and marks the smaller image in the other image.run plot.m)

灰度差分统计法提取图像纹理特征，包括平均值，对比度，熵，等特征，matlab函数，直接接使用，无需修改，中文注释，通俗易懂(Gray difference statistical method is used to extract texture features of image, including mean value, contrast, entropy, etc., matlab function, directly used without modification, Chinese annotation, and easy to understand)

说明：  ：基于主动轮廓识别和被动轮廓识别方法各自的优缺点，提出结合主动和被动的方法，先对图像进行被动轮廓的预处理，然 后再应用主动轮廓的方法，通过比较选出Canny算子进行预处理，再通过基于概率的方法分割图像，最后再应用Snake模型进行 轮廓提取。并取得较好的应用。(: Identification Based on Active Contour and passive contour recognition advantages and disadvantages of each method, proposed method of combining active and passive, passive first outline of the image pre-processing before applying the active contour method, by comparing the pre-selected Canny operator treatment, and then through the image segmentation method based on probability, and finally application of Snake model for contour extraction. And get better application.)