Automatic character location and segmentation in color scene images

Hao Wang
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引用次数: 20

Abstract

This paper describes a connected component (CC)-based approach to automatic text location and segmentation in natural scene images. A multi-group decomposition scheme is used to deal with the complexity of the color background. Connected component extraction is implemented using the block adjacency graph (BAG) algorithm after noise filtering and runlength smearing (RLS) operation. Some heuristic features and priority adaptive segmentation (PAS) of characters are proposed in block candidate verification and grayscale-based recognition. A prototype system is completed and the experimental results prove the effectiveness of the proposed method.
彩色场景图像中的自动字符定位和分割
本文提出了一种基于连接分量(CC)的自然场景图像文本自动定位和分割方法。采用多组分解方案处理彩色背景的复杂性。经过噪声滤波和运行长度涂抹(RLS)处理后,使用块邻接图(BAG)算法实现连通分量提取。在候选块验证和灰度识别中,提出了字符的启发式特征和优先级自适应分割(PAS)。实验结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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