Direct Processing of Run Length Compressed Document Image for Segmentation and Characterization of a Specified Block

Abstract

Extracting a block of interest referred to as segmenting a specified block in an image and studying its characteristics is of general research interest, and could be a challenging if such a segmentation task has to be carried out directly in a compressed image. This is the objective of the present research work. The proposal is to evolve a method which would segment and extract a specified block, and carry out its characterization without decompressing a compressed image, for two major reasons that most of the image archives contain images in compressed format and decompressing an image indents additional computing time and space. Specifically in this research work, the proposal is to work on run-length compressed document images.

7 Pages and Published with International Journal of Computer Applications (IJCA)

References in corpus (3)

• Extraction of Projection Profile, Run-Histogram and Entropy Features Straight from Run-Length Compressed Text-Documents
• Extraction of Line Word Character Segments Directly from Run Length Compressed Printed Text Documents
• Entropy Computation of Document Images in Run-Length Compressed Domain

Cited by in corpus (4)

• Spotting Separator Points at Line Terminals in Compressed Document Images for Text-line Segmentation
• Automatic Detection of Font Size Straight from Run Length Compressed Text Documents
• Direct Processing of Document Images in Compressed Domain
• Automatic Page Segmentation Without Decompressing the Run-Length Compressed Text Documents