为准确、高效地识别集装箱箱号,提出一种基于组合特征实现箱号识别的方法.对分割好的字符二值图像预处理后提取孔洞特征、凹凸特征、跳变特征、笔画特征等,利用树形分类器进行分类识别,并结合箱号自身的校验规则进行验证、识别.该方法不需要对字符图像做复杂的细化处理,提高了运算速度,避免了细化造成的字符畸变.实验结果表明,该方法平均箱号正确识别率可以达到93％,每箱号(1 1个字符)平均识别时间为0.065s.%In order to recognize container code precisely and effectively, a recognition method of container code based on combined features is proposed. After preprocessing the segmented binary image of single character, the character features including hole, concave-convex, leap, stroke, etc. Are extracted. Then the tree-like classifier is used to classify and recognize the container code, and combine the validation rules to verify the results. The method doesn' t need complex thinning procedure on the character image, improves the computational speed and avoids the character distortion. Experiment results show that the average recognition rate can reach 93% , and the recognition speed can reach 0.065 second per container code(including 11 characters).
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