Classification and compression of digital newspaper images

Wey-Wen Cindy Jiang; H. E. Meadows

doi:10.1117/12.157863

22 October 1993 Classification and compression of digital newspaper images

Wey-Wen Cindy Jiang, H. E. Meadows

Proceedings Volume 2094, Visual Communications and Image Processing '93; (1993) https://doi.org/10.1117/12.157863
Event: Visual Communications and Image Processing '93, 1993, Cambridge, MA, United States

Abstract

An improved scheme for newspaper block segmentation and classification is described. The newspaper image is first segmented into blocks using three passes of a run-length smoothing algorithm. Blocks may have any shape and need not be non-overlapped rectangles. The height H between the top-line and base-line of lower case letters, and the number of pixels that have values differing from their four neighboring pixels, are measured for simple and reliable block classification. Blocks of different types are compressed based on their own characteristics. Unlike conventional methods, halftone image blocks are treated differently from black and white graphic blocks for better compression. A lossless compression scheme for halftoned images is proposed. Reconstruction of gray-tones from halftone images employing information of both smooth and edgy areas is presented.

Citation Download Citation

Wey-Wen Cindy Jiang and H. E. Meadows "Classification and compression of digital newspaper images", Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); https://doi.org/10.1117/12.157863

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available