Algorithms for compressing compound document images with large text/background overlap

Bing-Fei Wu*, C. C. Chiu, Y. L. Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Two algorithms are presented for compressing image documents, with a high compression ratio for both colour and monochromatic compound document images. The proposed algorithms apply a new method of segmentation to separate the text from the image in a compound document in which the text overlaps the background. The segmentation method classifies document images into three planes: the text plane, the background (non-text) plane and the text's colour plane, each of which are processed using different compression techniques. The text plane is compressed using the pattern matching technique, called JB2. Wavelet transform and zerotree coding are used to compress the background plane and the text's colour plane. Assigning bits for different planes yields high-quality compound document images with both a high compression ratio and well presented text. The proposed algorithms greatly outperform two well known image compression methods, JPEG and DjVu, and enable the effective extraction of the text from a complex background, achieving a high compression ratio for compound document images.

Original languageEnglish
Pages (from-to)453-459
Number of pages7
JournalIEE Proceedings: Vision, Image and Signal Processing
Volume151
Issue number6
DOIs
StatePublished - 1 Dec 2004

Fingerprint Dive into the research topics of 'Algorithms for compressing compound document images with large text/background overlap'. Together they form a unique fingerprint.

Cite this