homework

基于YCgcr肤色空间的自适应阈值分割的算法，本人根据论文《YCgCr颜色空间的肤色聚类人脸检测法》原创(YCgcr color space based adaptive thresholding algorithm, I am under the thesis " YCgCr color clustering color space face detection method" original)

matlab相关矩阵操作及相关实例，MATLAB，即“矩阵实验室”，它是以矩阵为基本运算单元。(Matlab correlation matrix operations and related examples, MATLAB, that is, " Matrix Laboratory" , which is the matrix for the basic computing unit.)

说明：  灰色系统理论的灰色综合关联矩阵，et为大于阈值时的矩阵。(Gray gray system theory correlation matrix, et is greater than the threshold matrix.)

粒子群matlab程序，大家下载下来觉得好的话，一定要留言阿，包含粒子群优化，是用matlab编的。(PSO Matlab procedures, we feel good downloaded down, we must voice A, include PSO is using Matlab series.)

这是一个模糊算法的框架，只需修改模糊规则表，就可以移植到自己的工程中。(This is an algorithm of fuzzy algorithm framework, only need to modify the fuzzy rules table after can be transplanted to their own project.)

Reversible data / Logo Image Hiding using DCT.... Application has design using UI..

计算全通滤波器的源程序,根据信道群延迟,计算滤波器系数,用以校正信号相位变化(calculation of the all-pass filter source files, according to the channel group delay, filter coefficients calculated, for the correction signal phase changes)

用于数字信号处理的文件包 可模拟产生信号并进行FFT变换等作用(For digital signal processing package to simulate a signal and the FFT transform the role of)

matlab实用百例： 1-32是：图形应用篇 33-66是：界面设计篇 67-84是：图形处理篇 85-100是：数值分析篇(matlab practical one hundred cases: 1-32 is: papers 33-66 are graphical applications: interface design articles 67-84 are: graphics chapter 85-100 are: Numerical analysis of articles)

说明：  Edge detection result should be enhanced using linear method like Median filter to remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the centre of the pupil by counting the number of black pixels (zero value) of each column and row. Then get each row and column that has the maximum number of these black pixels. Then determine the center by simple calculation according to the image coordinate to set it correct on the image, consequently we can determine the radius of the pupil. Thus we can find the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms of circle and ellipse.