Scene Text Extraction Method Based on Clustering and MRF Model
Yuming Zhao · Jisuanji gongcheng · 2011
This paper proposes a method for extracting text regions from natural scene images.This method includes two parts,text region candidates extraction and candidate regions further classification of text region or non-text region.The text region candidates are extracted through a modified fuzzy C-means clustering algorithm combined with Laplacian mask and maximum gradient difference value,which involves texture features and HSL color space information.The candidate regions are checked by edge density information and shape information of the connected components based on Markov Random Field(MRF) model.The proposed method achieves reasonable accuracy for text extraction from examples of the ICDAR 2003 database.