Financial document image coding with regions of interest using JPEG2000

Abstract

Document image coding is a very important issue in document analysis and recognition systems providedwith vast samples. An image compression algorithm with Regions Of Interest (ROIs) using JPEG2000 is proposed for financial document images which have various categories, complex layouts, and irregular noises. Three types of ROIs: filled information ROIs, seal ROIs, and handwriting ROIs, are detected and extracted through document knowledge analysis and handwriting identification. The first ROIs are detected by document classification, the second are extracted by connected component analysis based on color and shape information, and the third are located by handwriting identification using an incremental Fisher linear discriminant classifier. A ROI mask with a random shape is constructed by thresholding and merging these ROIs. Finally, a financial document image is encoded using JPEG2000 Part 1 with this ROI mask. Compared to JPEG and DjVu, the method improves visual quality while decreasing storing space.