colorgrad

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

基于OpenCV的MPEG-7特征提取，c++代码(MPEG-7 feature extraction based on OpenCV)

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)

指纹图像的增强，效果很好,计算指纹的频率和方向，采用Gabor的方式增强(Fingerprint image enhancement, the effect is very good, calculate the frequency and direction of fingerprints, using Gabor way to enhance)

高效的文章分句算法程序,将由标点符号分开的语句的起始位置和结束位置记录到结构体里()

Image corrosion, swelling, binarization processing, image binary segmentation procedure matlab gui

Analysis of Singularities and Edge Detection using the Shearlet Transform

DCT数字水印基于CVI平台。用c编写的。(DCT digital watermarking)

自己写的双阈值分割算法，可以用在多个场合(Write their own dual-threshold segmentation algorithm can be used in a number of occasions)

matlab实现帧间差分提取运动目标，包含测试视频和运行效果。在背景固定的视频中效果较好。附赠lena图片以供CV学习。(Matlab achieves inter-frame differential extraction of moving objects, including testing video and running effects. It works well in video with fixed background. Enclosed Lena pictures for CV learning.)