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 language | English |
|---|---|
| Pages | II-176-II-180 |
| Publication status | Published - 2000 |
| Externally published | Yes |
| Event | 2000 TENCON Proceedings - Kuala Lumpur, Malaysia Duration: 2000 Sept 24 → 2000 Sept 27 |
Other
| Other | 2000 TENCON Proceedings |
|---|---|
| City | Kuala Lumpur, Malaysia |
| Period | 00/9/24 → 00/9/27 |
ASJC Scopus subject areas
- Computer Science Applications
- Electrical and Electronic Engineering