基于局部形状特征向量的场景图像字符匹配

Y. Hu, T. Nagao
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引用次数: 1

摘要

本文介绍了一种在平移、旋转、比例和对比度未知的复杂场景图像中定位和识别人物彩色图案的新方法。提出了一种局部形状特征向量模型。它由三个向量组成,表示字符模式中的一些可识别特征。该模型首先从未知目标图像中寻找潜在搜索点,并与其边缘图像进行匹配。然后,对候选点采用模板匹配技术,并采用简单的最近邻法对结果进行分类,最终在每个聚类中选出最佳匹配。因此,匹配和识别字符模式的多个实例。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。
Matching of characters in scene images by using local shape feature vectors
The paper describes a new method for locating and recognizing colored patterns of characters in complex scene images where translation, rotation, scale and contrast are unknown. A model of local shape feature vectors is presented. It consists of three vectors and represents some identifiable features in a pattern of characters. Based on this model, potential search points are first found from an unknown target image with this model matched to its edge image. Then, a template matching technique is employed on these candidate points, and the results are classified by a simple nearest neighborhood method and a best match is finally picked out in each cluster. Thus, multiple instances of a pattern of characters are matched and recognized. Experimental results demonstrate the effectiveness of this method.
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