Image Coding for Binary Document Based on the Regional Features

Author

Bo Yang ; Pengfei Li ; Liang Lei ; Xue Wang

Author_Institution

Sch. of Electron. Inf. Eng., Chongqing Univ. of Sci. & Technol., Chongqing, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

4

Abstract

Lossless coding is commonly found in binary image encoding with lower compression ratio. In this paper, image segmentation is used to classify the document image into line image regions, text image regions and halftone image regions. According to different features of each region, different encoding methods are applied to improve the image compression ratio. Adaptive arithmetic coding is used for line image regions, while symbols dictionary encoding for text image regions and the vector quantization coding for halftone image regions. Experiments show that this method can effectively improve the compression ratio of binary document image.

Keywords

adaptive codes; arithmetic codes; data compression; document image processing; image coding; image segmentation; vector quantisation; adaptive arithmetic coding; binary document; binary image encoding; halftone image regions; image coding; image compression ratio; image segmentation; line image regions; low compression ratio; symbols dictionary encoding; text image regions; vector quantization coding; Arithmetic; Codecs; Dictionaries; Image coding; Image segmentation; Information entropy; Information theory; Optical character recognition software; Stress; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5365186

Filename

5365186