AdaptiveThreshold函数

AdaptiveThreshold
自适应阈值方法

void cvAdaptiveThreshold( const CvArr* src, CvArr* dst, double max_value,
int adaptive_method=CV_ADAPTIVE_THRESH_MEAN_C,
int threshold_type=CV_THRESH_BINARY,
int block_size=3, double param1=5 );
src
输入图像.
dst
输出图像.
max_value
使用 CV_THRESH_BINARY 和 CV_THRESH_BINARY_INV 的最大值.
adaptive_method
自适应阈值算法使用：CV_ADAPTIVE_THRESH_MEAN_C 或 CV_ADAPTIVE_THRESH_GAUSSIAN_C （见讨论）.
threshold_type
取阈值类型：必须是下者之一
CV_THRESH_BINARY,
CV_THRESH_BINARY_INV
block_size
用来计算阈值的象素邻域大小: 3, 5, 7, ...
param1
与方法有关的参数。对方法 CV_ADAPTIVE_THRESH_MEAN_C 和 CV_ADAPTIVE_THRESH_GAUSSIAN_C， 它是一个从均值或加权均值提取的常数（见讨论）, 尽管它可以是负数。
函数 cvAdaptiveThreshold 将灰度图像变换到二值图像，采用下面公式：

threshold_type=CV_THRESH_BINARY:
dst(x,y) = max_value, if src(x,y)>T(x,y)
0, otherwise

threshold_type=CV_THRESH_BINARY_INV:
dst(x,y) = 0, if src(x,y)>T(x,y)
max_value, otherwise
其中 TI 是为每一个象素点单独计算的阈值

对方法 CV_ADAPTIVE_THRESH_MEAN_C，先求出块中的均值，再减掉param1。

对方法 CV_ADAPTIVE_THRESH_GAUSSIAN_C ，先求出块中的加权和(gaussian)， 再减掉param1。

 

例子：

 

/************cvAdaptiveThreshold Example************/

#include "highgui.h"
#include "cv.h"
#include <stdlib.h>
#include <stdio.h>

char wnd1[] = "in";
char wnd2[] = "out";

//读取trackbar上的两个值,实际两参数计算在on_track里
int _blocksize = 0;
int _param1 = 0;

IplImage *pImg = NULL;    //源图像
IplImage *pGray = NULL;   //灰度图
IplImage *pOut = NULL;    //二值图

void on_track(int position);  //trackbar回调函数

int main(int argc, char **argv)
{
    cvNamedWindow(wnd1, 1);
    cvNamedWindow(wnd2, 1);

    pImg = cvLoadImage(argv[1]);
    pGray = cvCreateImage(cvGetSize(pImg), IPL_DEPTH_8U, 1);
    pOut = cvCreateImage(cvGetSize(pImg), IPL_DEPTH_8U, 1);
    cvCvtColor(pImg, pGray, CV_RGB2GRAY);

    //创建两个滑动条
    cvCreateTrackbar("blocksize", wnd2, &_blocksize, 50, on_track);
    cvCreateTrackbar("param1", wnd2, &_param1, 100, on_track);

    cvShowImage(wnd1, pImg);
    cvWaitKey(0);

    cvReleaseImage(&pImg);
    cvReleaseImage(&pOut);
    cvReleaseImage(&pGray);
    cvDestroyWindow(wnd1);
    cvDestroyWindow(wnd2);

    return 0;
}

void on_track(int position)
{
    int blocksize = _blocksize * 2 + 3;     //计算阈值的像素邻域大小3,5,7...
    int param1 = _param1 - 50;    //被均值和加权均值减去的常量, 范围取[-50,50]

    cvAdaptiveThreshold(pGray,

                        pOut,

                        255,

                        CV_ADAPTIVE_THRESH_MEAN_C,

                        CV_THRESH_BINARY, blocksize, param1

                        );
    printf("blocksize: %d, param1: %d\n", blocksize, param1);
    cvShowImage(wnd2, pOut);
}