Support vector machines for text location in news video images

Author

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

Author_Institution

Comput. Graphics Lab., Sung Kyun Kwan Univ., Suwon, South Korea

Volume

2

fYear

2000

fDate

2000

Firstpage

176

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 an 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 an SVM can be trained to be a texture classifier. An 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

Keywords

image classification; image texture; learning automata; video signal processing; SVM-based method; digital video; multi-scale location; news video images; pixel classification; resized video images; support vector machines; text discrimination; text location; textural properties; texture classifier; Artificial intelligence; Computer graphics; Educational institutions; Feature extraction; Image texture analysis; Indexing; Layout; Pixel; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2000. Proceedings

Conference_Location

Kuala Lumpur

Print_ISBN

0-7803-6355-8

Type

conf

DOI

10.1109/TENCON.2000.888824

Filename

888824