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Camshift算法，即"Continuously Adaptive Mean-Shift"算法，是一种自适应的运动跟踪算法。它主要通过视频图像中运动物体的颜色信息来达到跟踪目的。(Camshift algorithm, namely " Continuously Adaptive Mean-Shift" algorithm is an adaptive motion tracking algorithm. It is primarily the color information of the object' s movement through the video images to achieve tracking purposes.)

【实例简介】图片转PDF

我改写后的graphbrian类，原本支持柱状图饼图和折线图的，现在添加了对这些图的风格调整，主要是增加了调整绘图区背景色和文本背景的功能，还增加了把图片保存为bmp文件的功能，以便用其他软件方便的打印。(I would then graphbrian category, which originally supported the pie chart histogram and line graph, and now added to adjust the style of these plans, the main adjustment is to increase the drawing area background color and text background function, but also an increase of the picture saved as bmp files, in order to use other software to facilitate printing.)

说明：  模式识别-贝叶斯最小错误率判别一幅图像是属于人，还是属于背景。图像经过预处理。(pattern recognition- Bayesian smallest error rate discriminant image is a person, or belong to the background. After pretreatment images.)

说明：  按照最邻近原则把待分类样本点分到各个簇。然后按平均法重新计算各个簇的质心，从而确定新的簇心。一直迭代，直到簇心的移动距离小于某个给定的值。(According to the nearest neighbor principle, the sample points to be classified are divided into clusters. Then the centroid of each cluster is recalculated according to the average method to determine the new cluster center. Iterate until the moving distance of the cluster center is less than a given value)

可同时实现多幅图片的傅里叶能量谱统计与分析！得到相应通道能量的信息！(Multiple images to achieve the power spectrum of Statistics and analysis!)

对两幅图像进行相似度计算，基于相似度计算进行模板匹配，带有测试图像，可以直接运行(Calculate the similarity of the two images, the similarity calculation based on template matching, with a test image, you can directly run)

说明：  NDVI最大值合成法批量计算Python代码(Python Code for Batch Computing by NDVI Maximum Composition Method)

加入乘性噪声和椒盐噪声的图像进行维纳滤波和均值滤波，采用不同窗口看效果(Add the image of multiplicative noise and salt and pepper noise for Wiener filtering and mean filtering, using different windows to see the effect)

基于LSB的音频水印嵌入提取算法，隐藏信息为一个文本文件(Extraction algorithm, the LSB-based audio watermark embedding hidden information into a text file)