meanshift-tracking

视频水印matlab源码，此为第二个压缩包，在水印领域的爱好者可以下载作为参考(Video Watermarking Matlab source, which is the second-compressed, Watermark in the field of lovers can download as a reference)

detection different object in video an moves with high accuracy

说明：  1.学习使用fft2,ifft2,fftshift,ifftshift函数。用fft2函数对”lena.bmp”做二维傅立叶变换，并显示其频谱，用fftshift函数将频谱坐标原点移动到图像中心。用ifft2函数做傅立叶反变换。（提示：显示频谱时，可以先对频谱取对数，这样可以压缩动态范围很大的频谱，获得更好的显示效果）(1. Learn to use fft2, ifft2, fftshift, ifftshift functions. With the FFT 2 function, the lena.bmp'The two-dimensional Fourier transform is performed and the spectrum is displayed. The origin of the spectrum coordinate is moved to the center of the image by using the FFT shift function. The inverse Fourier transform is done with ifft2 function. (Note: when displaying the spectrum, the logarithm of the spectrum can be taken first, so that the spectrum with a large dynamic range can be compressed to obtain better display effect.))

一种基于形貌特征识别圆形的方法，通过拟合圆方程来实现的经典hough变换方法(A method of Circle Recognition Based on morphological features is introduced. The classical Hough transform method is implemented by fitting the circle equation.)

matlab工具箱，用于构建和重建可分离的正交可操纵金字塔。(a matlab toolbox for building and reconstructing separable quadrature steerable pyramids.)

小型图像处理平台，包括滤波，边缘提取，边缘优化以及图像匹配功能(Small image processing platform, including filtering, edge detection, edge optimization and image matching function)

利用图像的不变矩以及模式识别的内容，构造三维飞机图像的矩特征，然后再利用D-S证据理论的改进方法 吸收法对图像进行融合 对飞机的型号进行匹配(Moment invariant of image and pattern recognition of the content, structure features three-dimensional plane images of the moment, and then use the improved DS evidence theory method of absorption of the fusion images to match the type of aircraft)

本文首先概述了独立成分分析与盲信号分离， 主成分分析的关系， 然后系统地介绍了该技术的基本概念和数据模型， 对现今比较流行的各种独立成分分析算法进行了剖析和总结。最后对独立成分分析的发展及应用前景作了展望(In this paper, an overview of independent component analysis and blind signal separation, principal component analysis of the relationship, and then systematically introduces the basic concept of the technology and data models for today' s more popular variety of independent component analysis algorithm is analyzed and summarized. Finally, independent component analysis of the development and application prospects are described)

Complete class-based image processing, contains all of the source code, auto image, There are cycle detection, periodic testing, MIT Artificial Intelligence Laboratory identification of the target source.

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