Question

场景是这样的，我有一个图像，我只想从中提取文本以进行进一步的OCR处理，我试图通过侵蚀和扩张来移除徽标但是当卡片在其背景中有图像时失败卡被分成2种不同的颜色，所以我想计算卡的直方图，然后过滤文本，因为它将在背景或任何其他非文本区域中具有最小峰值我得到这个opencv代码来计算直方图图像

OpenCV代码：

IplImage* trueColorImage = cvLoadImage("plastics.jpg");
TrueColorIplImg=[self CreateIplImageFromUIImage:trueColorImage];
IplImage* channel = cvCreateImage( cvGetSize(TrueColorIplImg), 8, 1);
IplImage *hist_img = cvCreateImage(cvSize(300,240), 8, 1);
cvSet( hist_img, cvScalarAll(255), 0 );
CvHistogram *hist_red;
CvHistogram *hist_green;
CvHistogram *hist_blue;
int hist_size = 256;      
float range[]={0,256};
float* ranges[] = { range };
float max_value = 0.0;
float max = 0.0;
float w_scale = 0.0;
hist_red = cvCreateHist(1, &hist_size, CV_HIST_ARRAY, ranges, 1);
hist_green = cvCreateHist(1, &hist_size, CV_HIST_ARRAY, ranges, 1);
hist_blue = cvCreateHist(1, &hist_size, CV_HIST_ARRAY, ranges, 1);
cvSetImageCOI(TrueColorIplImg,3);
cvCopy(TrueColorIplImg,channel);
cvResetImageROI(TrueColorIplImg);
cvCalcHist( &channel, hist_red, 0, NULL );
cvSetImageCOI(TrueColorIplImg,2);
cvCopy(TrueColorIplImg,channel);
cvResetImageROI(TrueColorIplImg);
cvCalcHist( &channel, hist_green, 0, NULL );
cvSetImageCOI(TrueColorIplImg,1);
cvCopy(TrueColorIplImg,channel);
cvResetImageROI(TrueColorIplImg);
cvCalcHist( &channel, hist_blue, 0, NULL );
cvGetMinMaxHistValue( hist_red, 0, &max_value, 0, 0 );
cvGetMinMaxHistValue( hist_green, 0, &max, 0, 0 );
max_value = (max > max_value) ? max : max_value;
cvGetMinMaxHistValue( hist_blue, 0, &max, 0, 0 );
max_value = (max > max_value) ? max : max_value;    
cvScale( hist_red->bins, hist_red->bins, ((float)hist_img->height)/max_value, 0 );
cvScale( hist_green->bins, hist_green->bins, ((float)hist_img->height)/max_value, 0 );
cvScale( hist_blue->bins, hist_blue->bins, ((float)hist_img->height)/max_value, 0 );
printf("Scale: %4.2f pixels per 100 units\n", max_value*100/((float)hist_img->height));                         
w_scale = ((float)hist_img->width)/hist_size;
 for( int i = 0; i < hist_size; i++ )
{
    cvRectangle( hist_img, cvPoint((int)i*w_scale , hist_img->height),
                cvPoint((int)(i+1)*w_scale, hist_img->height - cvRound(cvGetReal1D(hist_red->bins,i))),
                CV_RGB(255,0,0), -1, 8, 0 );
    cvRectangle( hist_img, cvPoint((int)i*w_scale , hist_img->height),
                cvPoint((int)(i+1)*w_scale, hist_img->height - cvRound(cvGetReal1D(hist_green->bins,i))),
                CV_RGB(0,255,0), -1, 8, 0 );
    cvRectangle( hist_img, cvPoint((int)i*w_scale , hist_img->height),
                cvPoint((int)(i+1)*w_scale, hist_img->height - cvRound(cvGetReal1D(hist_blue->bins,i))),
                CV_RGB(0,0,255), -1, 8, 0 );
}

Answer 1

生成直方图很简单，OpenCV文档中提供了代码。所以你并没有给我们任何有用的东西。剩下的任务就是真正的挑战所在。我很乐意看到你试图解决这个问题。

我从你的其他问题中注意到你对这个问题很感兴趣。我需要说解决它可能比你想象的要复杂一点。您可能希望限制您尝试解决的问题的范围，因为为所有类型的名片开发通用检测系统将是艰难的！

我做了一些研究，我将与您分享一些我发现的有趣材料：

如何从图像的直方图中过滤感兴趣的对象？

1 个答案: