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 conferencePaperpeer-review

9 Citations (Scopus)


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
Publication statusPublished - 2000
Externally publishedYes
Event2000 TENCON Proceedings - Kuala Lumpur, Malaysia
Duration: 2000 Sept 242000 Sept 27


Other2000 TENCON Proceedings
CityKuala Lumpur, Malaysia

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering


Dive into the research topics of 'Support vector machines for text location in news video images'. Together they form a unique fingerprint.

Cite this