Support vector machines for text location in news video images

Keechul Jung, Jung Hyun Han, Kwang In Kim, Se Hyun Park

Research output: Contribution to conferencePaper

9 Citations (Scopus)

Abstract

The aim of this paper is to show the applicability of support vector machines (SVMs) for the problem of text location and to propose a SVM-based method for locating texts in news video images. The proposed method is based on observations that texts in digital video have distinct textural properties that can be used to discriminate texts from the background and a SVM can be trained to be a texture classifier. A SVM is used for classifying a pixel into text or non-text by analyzing the textural properties of video image. To achieve multi-scale location, the video image is incrementally resized and the location process is performed over each of these resized images.

Original languageEnglish
PagesII-176-II-180
Publication statusPublished - 2000 Dec 1
Externally publishedYes
Event2000 TENCON Proceedings - Kuala Lumpur, Malaysia
Duration: 2000 Sep 242000 Sep 27

Other

Other2000 TENCON Proceedings
CityKuala Lumpur, Malaysia
Period00/9/2400/9/27

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Jung, K., Han, J. H., Kim, K. I., & Park, S. H. (2000). Support vector machines for text location in news video images. II-176-II-180. Paper presented at 2000 TENCON Proceedings, Kuala Lumpur, Malaysia, .