Direct Processing of Run Length Compressed Document Image for Segmentation and Characterization of a Specified Block
This work addresses a domain-specific challenge in document image processing by enabling efficient analysis of compressed archives, though it is incremental as it builds on existing compression techniques.
The paper tackles the problem of segmenting and characterizing a specified block directly in run-length compressed document images without decompression, achieving a method that reduces computing time and space by avoiding decompression.
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.