Speed-up Multi-modal Near Duplicate Image Detection

Chunlei  Yang; Jinye  Peng; Jianping  Fan

doi:10.4236/ojapps.2013.31B004

Chunlei Yang^*, Jinye Peng^*, Jianping Fan^*

Abstract: Near-duplicate image detection is a necessary operation to refine image search results for efficient user exploration. The existences of large amounts of near duplicates require fast and accurate automatic near-duplicate detection methods. We have designed a coarse-to-fine near duplicate detection framework to speed-up the process and a multi-modal integra-tion scheme for accurate detection. The duplicate pairs are detected with both global feature (partition based color his-togram) and local feature (CPAM and SIFT Bag-of-Word model). The experiment results on large scale data set proved the effectiveness of the proposed design.

Keywords: Near-Duplicate Detection; Coarse-To-Fine Framework; Multi-Modal Feature Integration

Cite this paper: C. Yang, J. Peng and J. Fan, "Speed-up Multi-modal Near Duplicate Image Detection," Open Journal of Applied Sciences, Vol. 3 No. 1, 2013, pp. 16-21. doi: 10.4236/ojapps.2013.31B004.

References

[1] Sebe, N., Lew, M., and Huijsmans, D. “Multi-scale sub-image search,” Proceedings of the seventh ACM international conference on Multimedia (Part 2) (1999), ACM, pp. 79–82.

[2] Wang, B., Li, Z., Li, M., and Ma, W. “Large-scale duplicate detection for web image search,” In Multimedia and Expo, 2006, pp. 353–356.

[3] Thomee, B., Huiskes, M., Bakker, E., and Lew, M. “Large scale image copy detection evaluation,” In Proceedings of the 1st ACM international conference on Multimedia information retrieval (2008), ACM, pp. 59–66.

[4] Tang, F., and Gao, Y. “Fast near duplicate detection for personal image collections,” In Proceedings of the 17th ACM international conference on Multimedia (2009), ACM, pp. 701–704.

[5] Wu, X., Ngo, C., Hauptmann, A., and Tan, H. “Real-time near-duplicate elimination for web video search with content and context,” IEEE Transactions on Multimedia 11, 2 (2009), 196–207.

[6] Jaimes, A., Chang, S., and Loui, A. “Detection of non-identical duplicate consumer photographs,” In Information, Communications and Signal Processing, 2003, vol. 1, IEEE, pp. 16–20.

[7] Zhang, D., and Chang, S. “Detecting image near-duplicate by stochastic attributed relational graph matching with learning,” In Proceedings of the 12th annual ACM international conference on Multimedia (2004), ACM, pp. 877–884.

[8] Tang, F., and Gao, Y. “Fast near duplicate detection for personal image collections,” In Proceedings of the 17th ACM international conference on Multimedia (2009), ACM, pp. 701–704.

[9] Jing, Y., Baluja, S., and Rowley, H. “Canonical image selection from the web,” In Proceedings of the 6th ACM international Conference on Image and Video Retrieval (2007), ACM, pp. 280–287.

[10] Ke, Y., Sukthankar, R., and Huston, L. “Efficient near-duplicate detection and sub-image retrieval,” In ACM Multimedia (2004), vol. 4, p. 5.

[11] Qiu, G. “Image coding using a coloured pattern appearance model,” In Visual Communication and Image Processing (2001).

[12] Lowe, D. “Distinctive image features from scale-invariant key points,” Interna-tional journal of computer vision 60, 2 (2004), 91–110.

[13] Wang, B., Li, Z., Li, M., and Ma, W. “Large-scale duplicate detection for web image search,” In Multimedia and Expo, 2006 IEEE International Con-ference on (2006), pp. 353–356.