Compression of smart contents with classification between text and picture blocks using sub-pixel gradient information

Chulhee Lee, Kyudong Kim, Hyuk Jae Lee

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a novel algorithm to classify complex-rendered text images by examining the color levels of the adjacent sub-pixels. The proposed algorithm is different from the previous approaches in that it uses the combined characteristics of RGB sub-channels, whereas the previous approaches use independent characteristics of RGB sub-channels. Experimental results demonstrate that the proposed algorithm improves the classification accuracy over the previous best algorithm by 15.9% for complex-rendered texts. Furthermore, the compression method optimized for text sub-images significantly reduces the computational complexity without degradation in compression efficiency.

Original languageEnglish
Pages (from-to)10-18
Number of pages9
JournalDisplays
Volume55
DOIs
Publication statusPublished - 2018 Dec

Bibliographical note

Funding Information:
This research was supported by the KIAT (Korea Institute for Advancement of Technology) grant funded by the Korea Government (MOTIE: Ministry of Trade Industry and Energy) (No. N0001883 , HRD Program for Intelligent semiconductor Industry) and also supported by the MOTIE (Ministry of Trade, Industry & Energy) ( 10080568 ) and KSRC (Korea Semiconductor Research Consortium) support program for the development of the future semiconductor device.

Publisher Copyright:
© 2018 Elsevier B.V.

All Science Journal Classification (ASJC) codes

  • Human-Computer Interaction
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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