关键词: 二值化, 区域检测, 字符分割, 字符识别, Psauvola

Abstract:

In order to solve the problem that the appearance size is similar, the actual vehicle type is different, this paper proposes the classification method of vehicles by identifying the number characters of bus body load. First of all, the two-value graph combined with the character’s format tower features to achieve the fine positioning of the text area, and the split-out number characters are identified by using a neural network, the result eventually translates the identified result into the corresponding bus category for model classification. The algorithm is tested on the samples of three-class or four-class buses collected at the dot, with a comprehensive recognition rate of 88.5%, which is nearly 10 percentage points than the model recognition based on the geometric features of the appearance, and the recognition rate based on the Psauvola algorithm is more than double compared with other binarization algorithms for character recognition.

Key words: binarization, area detection, character segmenting, character recognition, Psauvola