EMS表单中手写体中文识别图像预处理方法研究

目的在脱机手写体文字识别系统中,由于自由书写的字符不可避免地受到图像背景不均匀、图像倾斜和字符粘连及大小不一等因素的影响,为了确保字符切分和识别的正确性,对EMS表单中手写体汉字字符图像预处理方法进行探讨,展示了EMS表单图像预处理的全过程。方法采用最小二乘法作拟合直线的方法,对目标图像进行定位和分割,用基于大津阈值的分块阈值算法处理目标图像的背景不均问题,并减少噪声干扰。结果该图像预处理方法在1020张真实EMS图像上进行测试,识别正确率达到了86.3%。结论该方法有一定的灵活性和抗干扰性,减少了图像噪声对汉字字符切分和识别的影响。

An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration

This paper presents a methodology for off-line handwritten Chinese character recognition based on mergence of consecutive segments of adaptive duration. The handwritten Chinese character string is partitioned into a sequence of consecutive segments, which are combined to implement dissimilarity evaluation within a sliding window whose durations are determined adaptively by the integration of shapes and context of evaluations. The average stroke width is estimated for the handwritten Chinese character string, and a set of candidate character segmentation boundaries is found by using the integration of pixel and stroke features. The final decisions on segmentation and recognition are made under minimal arithmetical mean dissimilarities. Experiments proved that the proposed approach of adaptive duration outperforms the method of fixed duration, and is very effective for the recognition of overlapped, broken, touched, loosely configured Chinese characters.