tuxingbianhuan

rgb to HSV，很有用，调试成功，可以应用(rgb to HSV，#include "stdafx.h" #include <iostream.h> void main(float R, float G, float B, float& H, float& S, float&V) { // r,g,b values are from 0 to 1 // h = [0,360], s = [0,1], v = [0,1] // if s == 0, then h =-1 (undefined) float min, max, delta,tmp tmp = R>G?G:R min = tmp>B?B:tmp tmp = R>G?R:G max = tmp>B?tmp:B V = max // v delta = max- min if( max != 0 ) S = delta/max // s else { // r = g = b = 0 // s = 0, v is undefined S = 0 H = 0 return } if (delta == 0){ H = 0 return } else if(R == max){ if (G >= B) H = (G- B)/delta // between yellow & magenta else H = (G- B)/delta+ 6 } else if( G == max ) H = 2+ ( B- R )/delta // between cyan & yellow else if (B == ma)

使用大津法选定二值化阈值，并对彩色图像做二值化处理(Otsu binarization threshold is selected, and the color images do binarization processing)

一个选择模板的匹配方式，附带视觉标定,可以自由的选择模板进行匹配(A matching pattern of selected templates with visual calibration)

用VC++视觉检测程序，可以打开PCB板的照片文件，对其进行编辑、点运算、几何变换、正交变换、图像增强、形态变换、边缘与轮 廓检测、图像分析与复原、图像编码等功能。其中点运算包括图像反色、线性变换、阀值变换等功能；边缘检测包括Robert算子、 Sobel算子、Gauss-Laplace算子等；正交变换包括傅里叶变换、离散余弦变换、沃尔什变换；图像编码包括哈弗曼编码表、香农弗 曼编码表、行程编码、LZW编码等。 对于研究电子封装技术，视觉检测及电机精确控制的同学学习参考使用。(visual detecting for PCB.rar)

用AAM算法进行人脸特征点的标定，即对人脸的眼睛，眉毛，嘴巴，鼻子及脸的轮廓进行标记，此代码标记了68个特征点。(AAM algorithm for facial feature points calibration, calibration of this code is the 68 feature points, see the instance document.)

从Cbitmap派生的位图类，可通过指定一种颜色把一幅位图变透明，而它的使用差不多同Cbitamp一样简单。类中包含了两个文件：CISBitmap.cpp和CISBitmap.h，使用时附加进工程，可快速实现BMP位图图像的透明处理。(Cbitmap derived from the bitmap type, you can specify a color by a bitmap becomes transparent, and it s almost as simple as using the same Cbitamp. Class contains two files: CISBitmap.cpp and CISBitmap.h, into the use of additional works can be quickly processed to achieve a transparent bitmap BMP images.)

本程序可实现维纳滤波，可应用于反褶积等反问题的求解过程中，是非常简单实用的(This program can be realized Wiener filter can be applied to deconvolution inverse problems and the process is very simple and practical)

说明：  用canny算子来检测图像边缘，VC++(Using canny operator to detect image edge)

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)

说明：  双目测距bm算法，已经实现,基于vs2015+opencv3.2,测距精度很高，一米内精度一厘米误差(Binocular ranging bm algorithm, which has been implemented, is based on vs2015 + opencv3.2, which has high accuracy and one centimeter error in one meter)