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@ -227,46 +227,46 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, int index) {
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for (size_t i = 0; i < newSortedRect.size(); i++) {
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Rect mr = newSortedRect[i];
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Mat auxRoi(img_threshold, mr);
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//Mat auxRoi(img_threshold, mr);
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// 使用灰度图来截取图块，然后依次对每个图块进行大津阈值来二值化
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//Mat auxRoi(input_grey, mr);
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//Mat newRoi;
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//if (BLUE == plateType) {
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// /* img_threshold = auxRoi.clone();
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// int w = input_grey.cols;
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// int h = input_grey.rows;
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// Mat tmp = input_grey(Rect_<double>(w * 0.1, h * 0.1, w * 0.8, h * 0.8));
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// int threadHoldV = ThresholdOtsu(tmp);*/
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// threshold(auxRoi, newRoi, 5, 255, CV_THRESH_BINARY + CV_THRESH_OTSU);
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//}
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//else if (YELLOW == plateType) {
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// threshold(auxRoi, newRoi, 5, 255, CV_THRESH_BINARY_INV + CV_THRESH_OTSU);
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//}
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//else if (WHITE == plateType) {
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// threshold(auxRoi, newRoi, 5, 255, CV_THRESH_OTSU + CV_THRESH_BINARY_INV);
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//}
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//else {
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// threshold(auxRoi, newRoi, 5, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
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//}
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Mat auxRoi(input_grey, mr);
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Mat newRoi;
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if (BLUE == plateType) {
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/* img_threshold = auxRoi.clone();
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int w = input_grey.cols;
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int h = input_grey.rows;
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Mat tmp = input_grey(Rect_<double>(w * 0.1, h * 0.1, w * 0.8, h * 0.8));
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int threadHoldV = ThresholdOtsu(tmp);*/
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threshold(auxRoi, newRoi, 5, 255, CV_THRESH_BINARY + CV_THRESH_OTSU);
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}
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else if (YELLOW == plateType) {
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threshold(auxRoi, newRoi, 5, 255, CV_THRESH_BINARY_INV + CV_THRESH_OTSU);
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}
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else if (WHITE == plateType) {
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threshold(auxRoi, newRoi, 5, 255, CV_THRESH_OTSU + CV_THRESH_BINARY_INV);
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}
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else {
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threshold(auxRoi, newRoi, 5, 255, CV_THRESH_OTSU + CV_THRESH_BINARY);
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}
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// 归一化大小
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auxRoi = preprocessChar(auxRoi);
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newRoi = preprocessChar(newRoi);
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// 假设我们要重新训练ANN模型，在这里需要把训练样板输出
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if (i == 0) {
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stringstream ss(stringstream::in | stringstream::out);
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ss << "resources/image/tmp/debug_char_auxRoi_" << index << "_" << (i)
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<< ".jpg";
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utils::imwrite(ss.str(), auxRoi);
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utils::imwrite(ss.str(), newRoi);
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}
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// 每个字符图块输入到下面的步骤进行处理
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resultVec.push_back(auxRoi);
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resultVec.push_back(newRoi);
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}
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return 0;
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liuruoze
10 years ago