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@ -73,7 +73,7 @@ Mat CCharsSegment::preprocessChar(Mat in) {
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//! ×Ö·û·Ö¸îÓëÅÅÐò
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int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec) {
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int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec, int index) {
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if (!input.data) return 0x01;
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@ -135,7 +135,7 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec) {
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if (m_debug) {
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stringstream ss(stringstream::in | stringstream::out);
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ss << "resources/image/tmp/debug_char_threshold" << ".jpg";
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ss << "resources/image/tmp/debug_char_threshold_" << index << ".jpg";
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utils::imwrite(ss.str(), img_threshold);
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}
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@ -147,7 +147,7 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec) {
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if (m_debug) {
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stringstream ss(stringstream::in | stringstream::out);
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ss << "resources/image/tmp/debug_char_clearLiuDing" << ".jpg";
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ss << "resources/image/tmp/debug_char_clearLiuDing_" << index << ".jpg";
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utils::imwrite(ss.str(), img_threshold);
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}
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@ -184,22 +184,22 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec) {
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size_t specIndex = 0;
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//获得特殊字符对应的Rectt,如苏A的"A"
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// 获得特殊字符对应的Rectt,如苏A的"A"
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specIndex = GetSpecificRect(sortedRect);
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if (m_debug) {
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if (specIndex < sortedRect.size()) {
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Mat specMat(img_threshold, sortedRect[specIndex]);
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stringstream ss(stringstream::in | stringstream::out);
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ss << "resources/image/tmp/debug_specMat"
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ss << "resources/image/tmp/debug_specMat_" << index
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<< ".jpg";
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utils::imwrite(ss.str(), specMat);
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}
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}
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//根据特定Rect向左反推出中文字符
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//这样做的主要原因是根据findContours方法很难捕捉到中文字符的准确Rect，因此仅能
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//退过特定算法来指定
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// 根据特定Rect向左反推出中文字符
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// 这样做的主要原因是根据findContours方法很难捕捉到中文字符的准确Rect，因此仅能
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// 退过特定算法来指定
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Rect chineseRect;
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if (specIndex < sortedRect.size())
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chineseRect = GetChineseRect(sortedRect[specIndex]);
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@ -209,7 +209,7 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec) {
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if (m_debug) {
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Mat chineseMat(img_threshold, chineseRect);
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stringstream ss(stringstream::in | stringstream::out);
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ss << "resources/image/tmp/debug_chineseMat"
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ss << "resources/image/tmp/debug_chineseMat_" << index
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<< ".jpg";
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utils::imwrite(ss.str(), chineseMat);
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}
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@ -223,17 +223,49 @@ int CCharsSegment::charsSegment(Mat input, vector<Mat>& resultVec) {
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if (newSortedRect.size() == 0) return 0x05;
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// 开始截取每个字符
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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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// 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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// 归一化大小
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auxRoi = preprocessChar(auxRoi);
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if (m_debug) {
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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_" << (i)
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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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}
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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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}
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liuruoze
10 years ago