Experimental results show that the tree structure classifier is better than cascade classifier in both detection accuracy and computational efficiency.
实验表明，本文树形结构的车辆识别方法在识别率和识别速度上优于级联分类器，具有较好的实时性和一定的鲁棒性。
Most of non-text CCs are filtered out by cascade classifier and the remaining CCs are further verified by SVM. The final outputs are binary images containing texts only.
由于文本连通分量和非文本连通分量在特征上存在差异，大多数非文本会被级联分类器丢弃，而SVM则能在此结果上做进一步的验证，因此最终输出只有文本的二值图像。
Most of non-text CCs are filtered out by cascade classifier and the remaining CCs are further verified by SVM. The final outputs are binary images containing texts only.
由于文本连通分量和非文本连通分量在特征上存在差异，大多数非文本会被级联分类器丢弃，而SVM则能在此结果上做进一步的验证，因此最终输出只有文本的二值图像。
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