Hybrid approach to efficient text extraction in complex color images.

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22
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SCOPUS

32

초록

Texture-based methods and connected component (CC) methods have been widely used for text localization. However, these two primary methods have their own strength and weakness. This paper proposes a hybrid approach of the two methods for text localization in complex images. An automatically constructed MLP-based texture classifier can increase the recall rates for complex images with much less user intervention and no explicit feature extraction. The CC-based filtering based on the geometry and shape information enhances the precision rates without affecting overall performance. Then, the time-consuming texture analysis for less relevant pixels is avoided by using CAMShift. Our experimentation shows that the proposed hybrid approach leads to not only robust but also efficient text localization. (C) 2004 Elsevier B.V. All rights reserved.

키워드

content-based image indexing; texture; connected component; text localization multi-layer perceptron (MLP); X-Y recursive cut; mean shift; CAMShift; NEURAL-NETWORK; VIDEO; LOCATION; IDENTIFICATION; SYSTEM
제목
Hybrid approach to efficient text extraction in complex color images.
저자
Jung, K; Han, JH
DOI
10.1016/j.patrec.2004.01.017
발행일
2004-04-19
유형
Article
저널명
Pattern Recognition Letters
권
25
호
6
페이지
679 ~ 699