Summarization of JBIG2 Compressed Indian Language Textual Images
Utpal Garain, Asoke Kumar Datta, Ujjwal Bhattacharya, Swapan Kr. Parui · 2006
This paper presents a method for automatic summarization of JBIG2 coded textual images without optical character recognition (OCR). Compressed images are partially (less than 10% of the uncompressed image size) decompressed and text lines and words are marked. A few features are computed at each sentence level. Based on the feature values sentences are then marked as a summary sentence or not. The system finally generates a set of sentences as summary. In addition, sentences are ranked within the summary. Experiment considers Indian language text images. Test results show a sentence selection efficiency of about 56% when judged against summarization generated by human. A nonparametric (distribution-free) rank statistic shows a correlation coefficient of 0.28 as a measure of the (minimum) strength of the associations between sentence ranking by machine and human.