project

这个文件包里包含了几乎所有的聚类的工具箱，包含采用混合高斯模型的运动物体检测方面的源代码。(This document contains the bag almost all the clustering of the toolbox, including the use of Gaussian Mixture Model of Moving Objects for testing source code.)

水声鼻祖Urick经典著作：水声原理。超星版，方便阅读(Originator Urick classic acoustic: acoustic principles. Superstar version, easy to read)

高斯平滑滤波实例，高斯滤波实质上是一种信号的滤波器，其用途是信号的平滑处理，我们知道数字图像用于后期应用，其噪声是最大的问题，，由于误差会累计传递等原因，很多图像处理教材会在很早的时候介绍Gauss滤波器，用于得到信噪比SNR较高的图像（反应真实信号）。 (Instance of the Gaussian smoothing filter, Gaussian filter is essentially a signal filter, its purpose is to smooth processing of the signal, we know that the digital image for the late application, the noise is the biggest problem, the error accumulated transfer reason, a lot of image processing textbooks will be introduced at an early Gauss filter for higher SNR of the image (real response signal).)

水平集代码和论文，图像分割,快速有效的图像分割方法(code and paper about level set,image segmentation)

1.打开左右两张影像2.Harris算法提取同名点3.显示提取同名点（若要进行下一步匹配则不建议显示，这里只是用于查看是否提取出）4.相关系数匹配（只在找出的同名点内匹配）5.LSM最小二乘匹配（先进行粗匹配，再精匹配）(1 Open the left and right images 2.Harris algorithm to extract two tie points 3 shows the extraction of corresponding points (not recommended to proceed to the next match show, here is used to see if extracted) 4. Correlation coefficient matching (just looking match within a point of the same name) 5.LSM least squares matching (rough first match, then fine match))

采用surf算法对两幅较低重叠度的图像进行拼接(Image mosaic using surf algorithm)

去散射和边缘增强是水下图像从严重细节损失、颜色偏移和模糊中提取的关键步骤。本文提出了一种增强水下图像对比度和边缘的新方法。(De-scattering and edge enhancing are critical procedures for underwater images which surfer from serious detail loss, color deviation and blurring. In this work, a novel method has been proposed to enhance contrast and edge of underwater images.)

这是我们自己做的一套投影仪标定程序，反投影精度在1个象素之内(This is to do our own set of projector calibration procedures, back-projection at a pixel accuracy of)

这是完整的一套人脸表情识别,从样本训练到目标的识别.采用PCA来提取特征(This is the complete set of Facial Expression Recognition from the sample to the target identification training. Using PCA to extract the characteristics of)

模式识别中相似度-豪斯多夫距离源码,可用于对比算法相似度，也可直接作为函数调用(Hausdorff distance for pattern recognition similarity calculating)