Document image compression using straight line extraction and block context model

• Published in: International Conference on Image Processing Vol. 1; pp. 530 - 534 vol.1
• Main Authors: Hwayong Joung, Wong, E.K., Yu Chen, Kim, S.P.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 1998
• Subjects: Context modeling; Data mining; Engineering drawings; Image coding; Image segmentation; Information science; Merging; Morphology; Vector quantization; White spaces
• ISBN: 0818688211; 9780818688218
• DOI: 10.1109/ICIP.1998.723555

We present a new lossy technique for document image compression by using straight line extraction and a block context model. Straight line segments are extracted from a binary document image and subtracted from the original image. Their endpoint coordinates and width can then be efficiently coded. The remaining part of the image, which mainly contains text and other symbols, is coded using a high-order block context model (HOBCM) based on vector quantization (VQ). The proposed method is particularly effective for document images containing a large number of straight line segments, such as engineering or architectural drawings. It achieves much higher compression than conventional lossless techniques, such as the JBIG and CCITT G3 and G4 standards, with little loss of visual quality. In the experiments we carried out, a group of engineering drawings digitized at 200 dpi, compression ratios ranging from 30 to 70 were obtained.