fatigue_mq_block

利用直方图双峰法选取适当阈值对图像进行二值化处理。此法只适用于直方图为双峰状图像。(Using the Shuangfeng method to the appropriate threshold histogram of image processing two values. This method is only applicable to the histogram of image of Shuangfeng.)

双目视觉经验总结，希望后面的不要犯错误。(Binocular visual experience summary, make no mistake behind.)

mfc图像处理，实现图像的配准，自己编写，可以应用(mfc image processing, image registration)

比较新的图像处理类，2010版，并且有DEMO,方便应该(Relatively new class of image processing, 2010 Edition, and has DEMO, should facilitate)

imnoise的M文件，对数字图像的加噪声非常有用处！(imnoise M-files, plus noise on digital images is very useful!)

基于otsu的自适应阀值canny边缘检测(adaptive canny edge detection based on otsu)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)

源码包括了常用的图像处理方法，代码详细，适合初学者(Source code, including the commonly used image processing method, the code in detail, suitable for beginners)

《基于计算机视觉的普适性三维重建方法研究》源代码，实现了一种将二维图像重建成三维场景的方法。(Source code of <General Sense Three-Dimension Reconstruction Research Based on Computer Vision>, a technique which can convert 2D images into 3D sence.)

匹配算法，可以完美运行，对于初学者有着很好的参考价值(Matching algorithm, can be a perfect run, has a very good reference for beginners)