bayeserzhi

经典的边缘检测算法Sobel matlab源码(classic edge detection algorithm Sobel Matlab FOSS)

MATLAB初学者容易碰到的问题的相关解答，适合初学者的学习。(MATLAB for beginners easy to encounter problems related to answer, for beginners to learn.)

matlab仿真程序，适合初学者，比较实用，可用性高。(matlab simulation program, suitable for beginners, more practical, high-availability.)

1.O——Hungarian.m 主要功能： 实现匈牙利算法，最终产生关联矩阵 2.trackassoicataion_hgm 主要功能： 1）实现两个传感器对三条航迹的估计； 2）实现两个传感器三组数据的关联； 3）统计误关联-步数的关系，画出结果图。(1.O- Hungarian.m The main function: Hungarian algorithm to achieve, ultimately produce correlation matrix 2.trackassoicataion_hgm The main function: 1) to achieve two sensors estimate of three tracks 2) to achieve the two sensors associated with the three sets of data 3) statistical error associated with- relationship the number of steps, the results shown in Fig.)

二进制和十进制互相转换，比自带的更加方便(Each binary and decimal conversion, more convenient than the native)

机器人仿真程序，有界面和运行系统，供初学者学习(robot simulator，just for preliminary learner to study。Thank you very much。haha )

LOWESS, Locally Weighted Scatterplot Smoothing for linear and non-linear data (enhanced)( LOWESS- Locally Weighted Scatterplot Smoothing Modifications: This regression will work on linear and non-linear relationships between X and Y.)

说明：  软测量氧含量数据工况聚类、建模matlab实现代码2(Measuring the oxygen content of soft data clustering conditions, modeling the implementation code 2 matlab)

加窗傅立叶变换及其逆变换的重构，并有详细的注释和例子(Windowed Fourier transform and its inverse transform of the reconstruction, and detailed notes and examples)

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.