Binarization of stone inscripted documents

Conversion of stone images with inscription to binary form pose several challenges due to perspective distortion, minimal distinction between foreground and background, lack of standardization of the text size and shape, less discernible color difference between the foreground and background and highly correlated noises. Traditional techniques to convert these images to binary form fail to handle all these challenges efficiently. In this paper we present a new technique to convert images of stone with inscriptions to binary forms. Initially, the Fast ICA (Independent Component Analysis) technique is used to enhance the minimal difference between text and non-text regions by decreasing the correlated noises. Then, the image is normalized using linear regression method. Cumulative residual entropy is obtained from the normalized image and it is analyzed to get threshold value to be used for conversion to binary image. The proposed technique is tested on images collected from world heritage site, "Hampi" and compared to other existing algorithms for binary conversion. The results of the proposed method are better than the competing algorithms.