An adaptive technique for global and local skew correction in color documents

In this paper, a new technique is proposed for global and local skew detection in complex color documents. The proposed technique, which can be applied also to grayscale and binary documents, consists of four main stages; color reduction, text localization, document binarization and skew correction. Color reduction limits the initial number of colors to a small number, usually smaller than 10 colors. Thus, the original documents are decomposed in homogenous regions. Text localization initially divides the document into a number of binary planes (color planes) equal to the number of the reduced colors. Then, connected component analysis is performed and text is extracted according to similarity features between adjacent connected components. In the third stage the binary document is composed by the processed binary planes. Finally, skew correction is achieved by detecting the direction of connection of the connected components in the binary images. The proposed technique has been extensively tested with two databases, one with complex scanned color cover books and another with grayscale scanned newspapers taken from the database of the university of Oulu. Experimental results are provided and prove the effectiveness of the proposed technique.