Binarization Method for the Document Images with Local Highlight Interference
Sun Jie-di · Guangdian gongcheng · 2012
A novel binarization method for document images based on Curvelet transform is presented.The interference caused by local high lightness is eliminated to get a better image quality.Firstly,the Curvelet transformation is applied to the document images with local high lightness area,and the Curvelet coefficients can be got.Then,according to the feature of images represented by Curvelet coefficients,the Curvelet coefficients are enhanced nonlinearly to optimize the histogram distribution.Curvelet coefficients are transformed inversely to get the images,and then the Otsu method is applied to get the binary image.According to the binarized image,the OCR recognition results are got by the ABBYY FineReader10.Experimental results show that the highest recognition accuracy of characters could reach 94.81%.The performance of this method is better than the other four typical binarization methods.