iOS+Tesseract Ocr+OpenCV

Question

我为iOS写了一个数字OCR。我有一个测试图像png与两位数5和4。我找到轮廓了。我如何在Tesseract转乘等高线？

初始化tesseract：

    tess = new tesseract::TessBaseAPI();
    tess->Init([dataPath cStringUsingEncoding:NSUTF8StringEncoding], "eng");
    tess->SetPageSegMode(tesseract::PSM_SINGLE_CHAR); //<-- !!!!
    tess->tesseract::TessBaseAPI::SetVariable("tessedit_char_whitelist", "0123456789");

用于检测轮廓的函数：

- (std::vector<std::vector<cv::Point> >)findSquaresInImage:(cv::Mat)_image {
std::vector<std::vector<cv::Point> > squares;
cv::Mat pyr, timg, gray0(_image.size(), CV_8U), gray;
int thresh = 50, N = 11;
cv::pyrDown(_image, pyr, cv::Size(_image.cols/2, _image.rows/2));
cv::pyrUp(pyr, timg, _image.size());
std::vector<std::vector<cv::Point> > contours;
    int ch[] = {0, 0};
    mixChannels(&timg, 1, &gray0, 1, ch, 1);
    for( int l = 0; l < N; l++ ) {
        if( l == 0 ) {
            cv::Canny(gray0, gray, 0, thresh, 5);
            cv::dilate(gray, gray, cv::Mat(), cv::Point(-1,-1));
        }
        else {
            gray = gray0 >= (l+1)*255/N;
        }
        cv::findContours(gray, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
        std::vector<cv::Point> approx;

        CvRect rec1;
        std::string str;
        std::map<int,IplImage*> pic_list;

        for( size_t i = 0; i < contours.size(); i++ )
        {

            rec1 = cv::boundingRect(contours[i]);

            if (rec1.height > 0.5*gray.rows && rec1.width < 0.756*gray.cols) {
                NSLog(@"%d %d %d %d", rec1.width, rec1.height, rec1.x, rec1.y);
                cv::approxPolyDP(cv::Mat(contours[i]), approx, arcLength(cv::Mat(contours[i]), true)*0.02, true);
                squares.push_back(approx);
            }
        }
    }

return squares;  }

cv::Mat debugSquares( std::vector<std::vector<cv::Point> > squares, cv::Mat image ) {
for ( int i = 0; i< squares.size(); i++ ) {
    // draw contour
    cv::drawContours(image, squares, i, cv::Scalar(255,0,0), 1, 8, std::vector<cv::Vec4i>(), 0, cv::Point());

    // draw bounding rect
    cv::Rect rect = boundingRect(cv::Mat(squares[i]));
    cv::rectangle(image, rect.tl(), rect.br(), cv::Scalar(0,255,0), 2, 8, 0);

    // draw rotated rect
    cv::RotatedRect minRect = minAreaRect(cv::Mat(squares[i]));
    cv::Point2f rect_points[4];
    minRect.points( rect_points );
    for ( int j = 0; j < 4; j++ ) {
        cv::line( image, rect_points[j], rect_points[(j+1)%4], cv::Scalar(0,0,255), 1, 8 ); // blue
    }
}

return image;
}

- (IBAction)onMath:(id)sender {
    UIImage *image = [UIImage imageNamed:@"test1.png"];

    cv::Mat iMat = [self cvMatFromUIImage:image];
    std::vector<std::vector<cv::Point> > sq = [self findSquaresInImage:iMat];
    cv::Mat hui = debugSquares(sq, iMat);

    image = [self UIImageFromCVMat:hui];
    self.imView.image = image;
}

GitHub项目链接：https://github.com/maxpatsy/iorc

Answer 1

你能在这里查一下这个答案吗

我在这里描述了为Tesseract准备图像的一些技巧：使用Tesseract识别车牌

在你的例子中，有几件事正在发生...