OpenCV_图像二值化

  对图像进行二值化的关键函数为cvThreshold，它采用Canny方法对图像进行边缘检测：

void cvThreshold (
    const CvArr *src, CvArr *dst, double threshold,
    double max_value, int threshold_type );

参数src表示输入图像，必须为单通道灰度图；参数dst表示输出的边缘图像，为单通道黑白图；参数threshold表示阈值；参数max_value表示最大值；参数threshold_type表示运算方法，在OpenCV的imgproc\types_c.h中可以找到运算方法的定义：

enum { /* Threshold types */
    CV_THRESH_BINARY     = 0, /* value = value > threshold ? max_value : 0     */
    CV_THRESH_BINARY_INV = 1, /* value = value > threshold ? 0 : max_value     */
    CV_THRESH_TRUNC      = 2, /* value = value > threshold ? threshold : value */
    CV_THRESH_TOZERO     = 3, /* value = value > threshold ? value : 0         */
    CV_THRESH_TOZERO_INV = 4, /* value = value > threshold ? 0 : value         */
    CV_THRESH_MASK       = 7,
    /* use Otsu algorithm to choose the optimal threshold value;
       combine the flag with one of the above CV_THRESH_* values */
    CV_THRESH_OTSU       = 8
};

代码如下：

#include 

IplImage *g_pGrayImage = NULL;
IplImage *g_pBinaryImage = NULL;
const char *pstrWindowsBinaryTitle = "二值图";

void on_trackbar ( int pos ) {
    /* 转为二值图 */
    cvThreshold ( g_pGrayImage, g_pBinaryImage, pos, 255, CV_THRESH_BINARY );
    cvShowImage ( pstrWindowsBinaryTitle, g_pBinaryImage ); /* 显示二值图 */
}

int main ( int argc, char **argv ) {
    const char *pstrWindowsSrcTitle = "原图";
    const char *pstrWindowsToolBarName = "二值图阈值";

    IplImage *pSrcImage = cvLoadImage ( "zzjb.jpg", CV_LOAD_IMAGE_UNCHANGED ); /* 从文件中加载原图 */
    /* 转为灰度图 */
    g_pGrayImage = cvCreateImage ( cvGetSize ( pSrcImage ), IPL_DEPTH_8U, 1 );
    cvCvtColor ( pSrcImage, g_pGrayImage, CV_BGR2GRAY );
    g_pBinaryImage = cvCreateImage ( cvGetSize ( g_pGrayImage ), IPL_DEPTH_8U, 1 ); /* 创建二值图 */
    /* 显示原图 */
    cvNamedWindow ( pstrWindowsSrcTitle, CV_WINDOW_AUTOSIZE );
    cvShowImage ( pstrWindowsSrcTitle, pSrcImage );
    cvNamedWindow ( pstrWindowsBinaryTitle, CV_WINDOW_AUTOSIZE ); /* 创建二值图窗口 */
    /* 滑动条 */
    int nThreshold = 0;
    cvCreateTrackbar ( pstrWindowsToolBarName, pstrWindowsBinaryTitle, &nThreshold, 254, on_trackbar );
    on_trackbar ( 1 );
    cvWaitKey ( 0 );
    cvDestroyWindow ( pstrWindowsSrcTitle );
    cvDestroyWindow ( pstrWindowsBinaryTitle );
    cvReleaseImage ( &pSrcImage );
    cvReleaseImage ( &g_pGrayImage );
    cvReleaseImage ( &g_pBinaryImage );
    return 0;
}

OpenCV还有个cvAdaptiveThreshold函数，这个函数会使用Otsu算法(大律法或最大类间方差法)来计算出一个全局阈值，然后根据这个阈值进行二值化。