Title :
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
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;
Conference_Titel :
TENCON 2000. Proceedings
Conference_Location :
Kuala Lumpur
Print_ISBN :
0-7803-6355-8
DOI :
10.1109/TENCON.2000.888824
