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Robust Text Detection and Extraction in Natural Scene Images using Conditional Random Field Model and OCR


Author : Pratik Yadav and Prabhudev Irabashetti

Pages : 3784-3787
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Abstract

In Natural Scene Image, Text detection is important tasks which are used for many content based image analysis. A maximally stable external region based method is used for scene detection .This MSER based method has stages character candidate extraction, text candidate construction, text candidate elimination & text candidate classification. In this systems the method are not focus on how to detect highly blurred text in low resolution natural scene images. The current technology not any text extraction method provided. In proposed system by using Connected Component analysis a Conditional Random field (CRF) model is used to assign candidate component as one of the two classes (text& Non Text) by Considering both unary component properties and binary contextual component relationship. For this purpose we are using connected component analysis method. The proposed system also performs a text extraction using OCR.

Keywords: Maximally stable Extremal Region, Text candidates Construction, Text Candidate Elimination, text Candidate Classification, Connected Component Analysis, Optical Character recognition

Article published in International Journal of Current Engineering and Technology, Vol.5, No.6 (Dec-2015)

 

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