基于多尺度图匹配核的场景单字识别方法（英文）

被引：2

作者：

史存召 ^{[1
]}

王春恒 ^{[1
]}

肖柏华 ^{[1
]}

张阳 ^{[2
]}

高嵩 ^{[1
]}

机构：

[1] The State Key Laboratory of Management and Control of Complex Systems,Institute of Automation,Chinese Academy of Scences

[2] Kuyun Interactive Technology Limited

来源：

自动化学报 | 2014年 / 40卷 / 04期

关键词：

Character recognition; structure; graph-matching; energy; kernel; histograms of oriented gradients(HOG); support vector machine(SVM);

D O I：

暂无

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

Recognizing characters extracted from natural scene images is quite challenging due to the high degree of intraclass variation. In this paper, we propose a multi-scale graph-matching based kernel for scene character recognition. In order to capture the inherently distinctive structures of characters, each image is represented by several graphs associated with multi-scale image grids. The similarity between two images is thus defined as the optimum energy by matching two graphs(images), which finds the best match for each node in the graph while also preserving the spatial consistency across adjacent nodes. The computed similarity is suitable to construct a kernel for support vector machine(SVM). Multiple kernels acquired by matching graphs with multi-scale grids are combined so that the final kernel is more robust. Experimental results on challenging Chars74k and ICDAR03-CH datasets show that the proposed method performs better than the state of the art methods.

引用

页码：751 / 756

页数：6