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A Text Detection Method Using Wavelet Packet Analysis and Unsupervised Classifier  

Lee, Geum-Boon (Dept. of Computer Engineering, Graduate School, Chosun University)
Odoyo Wilfred O. (Dept. of Computer Engineering, Graduate School, Chosun University)
Kim, Kuk-Se (Dept. of Computer Engineering, Graduate School, Chosun University)
Cho, Beom-Joon (Dept. of Computer Engineering, Graduate School, Chosun University)
Publication Information
Journal of information and communication convergence engineering / v.4, no.4, 2006 , pp. 174-179 More about this Journal
Abstract
In this paper we present a text detection method inspired by wavelet packet analysis and improved fuzzy clustering algorithm(IAFC).This approach assumes that the text and non-text regions are considered as two different texture regions. The text detection is achieved by using wavelet packet analysis as a feature analysis. The wavelet packet analysis is a method of wavelet decomposition that offers a richer range of possibilities for document image. From these multi scale features, we adapt the improved fuzzy clustering algorithm based on the unsupervised learning rule. The results show that our text detection method is effective for document images scanned from newspapers and journals.
Keywords
document image segmentation; wavelet packet analysis; improved fuzzy clustering algorithm;
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