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ISSN: 1549-3636 (Print)
ISSN: 1552-6607 (Online)
Research Article Open Access

Video Retrieval using Histogram and Sift Combined with Graph-based Image Segmentation

Tran Quang Anh, Pham Bao, Tran Thuong Khanh, Bui Ngo Da Thao, Tran Anh Tuan and Nguyen Thanh Nhut

Abstract

Problem statement: Content-Based Video Retrieval (CBVR) is still an open hard problem because of the semantic gap between low-level features and high-level features, largeness of database, keyframe’s content, choosing feature.In this study we introduce a new approach for this problem based on Scale-Invariant Feature Transform (SIFT) feature, a new metric and an object retrieval method. Conclusion/Recommendations: Our algorithm is built on a Content-Based Image Retrieval (CBIR) method in which the keyframe database includes keyframes detected from video database by using our shot detection method. Experiments show that the approach of our algorithmhas fairly high accuracy.

Journal of Computer Science
Volume 8 No. 6, 2012, 853-858

DOI: https://doi.org/10.3844/jcssp.2012.853.858

Submitted On: 12 January 2012 Published On: 15 March 2012

How to Cite: Anh, T. Q., Bao, P., Khanh, T. T., Thao, B. N. D., Tuan, T. A. & Nhut, N. T. (2012). Video Retrieval using Histogram and Sift Combined with Graph-based Image Segmentation. Journal of Computer Science, 8(6), 853-858. https://doi.org/10.3844/jcssp.2012.853.858

Open AccessCopyright: © 2012 Tran Quang Anh, Pham Bao, Tran Thuong Khanh, Bui Ngo Da Thao, Tran Anh Tuan and Nguyen Thanh Nhut. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Content-Based Video Retrieval (CBVR)
  • Content-Based Image Retrieval (CBIR)
  • Scale-Invariant Feature Transform (SIFT)
  • natural important problem
  • various properties