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Hybrid Approach of Texture and Connected Component Methods for Text Extraction in Complex Images  

정기철 (숭실대학교 정보과학대학 미디어학부)
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Abstract
We present a hybrid approach of texture-based method and connected component (CC)-based method for text extraction in complex images. Two primary methods, which are mainly utilized in this area, are sequentially merged for compensating for their weak points. An automatically constructed MLP-based texture classifier can increase recall rates for complex images with small amount of user intervention and without explicit feature extraction. CC-based filtering based on the shape information using NMF enhances the precision rate without affecting overall performance. As a result, a combination of texture and CC-based methods leads to not only robust but also efficient text extraction. We also enhance the processing speed by adopting appropriate region marking methods for each input image category.
Keywords
Text Extraction; MLP; Texture; NMF(Non-negative Matrix Factorization); Connected Component(CC); CAMShift;
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