International Journal of Applied Science and Engineering
Published by Chaoyang University of Technology

Chung-Wei Liang and Po-Yueh Chen*

Department of Computer Science and Information Engineering, Chaoyang University of Technology, Wufeng, Taichung county 413, Taiwan, R.O.C.

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This paper presents an efficient yet simple method to extract text regions from static images or video sequences. The operation speed of Haar discrete wavelet transform (DWT) operates the fastest among all wavelets because its coefficients are either 1 or -1. This is one of the reasons we employ Haar DWT to detect edges of candidate text regions. The resulted detail component sub-bands contain both text edges and non-text edges. However, the intensity of the text edges is different from that of the non-text edges. Therefore, we can apply thresholding to preliminary remove the non-text edges. Text regions are composed of vertical edges, horizontal edges and diagonal edges. Morphological dilation operators are applied to connect isolated text edges of each detail component sub-band in a transformed binary image. According to the experiment results, real text regions are the overlapped portion of three kinds of dilated edges. Hence, we can apply the logical AND operator to three kinds of dilated edges and obtain the final text regions correctly.

Keywords: text extraction; Haar DWT; Thresholding; Morphological operator; Logical AND operator.

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Accepted: 2004-02-20
Available Online: 2004-03-02

Cite this article:

Liang , C.-W., Chen, P.-Y. 2004. DWT based text localization, International Journal of Applied Science and Engineering, 2, 105–116.