Abstract
As large amount of visual Information is available on web in form of images, graphics, animations and videos, so it is important in internet era to have an effective video search system. As there are number of video search engine (blinkx, Videosurf, Google, YouTube, etc.) which search for relevant videos based on user “keyword” or “term”, But very less commercial video search engine are available which search videos based on visual image/clip/video. In this paper we are recommending a system that will search for relevant video using color feature of video in response of user Query.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Choras, R.S.: Image Feature Extraction Techniques and Their Applications for CBIR and Biometrics Systems. International Journal of Biology and Biomedical Engineering 1(1), 7–16 (2007)
Yang, Y., Lovel, B.C., et al.: Content-Based Video Retrieval (CBVR) System for CCTV Surveillance Videos. In: Proceeding DICTA 2009 Proceedings of the 2009 Digital Image Computing: Techniques and Applications, pp. 183–187. IEEE Computer Society, Washington, DC (2009)
Darrel, A.P.A.: Cooperative robust estimation using layers of support. T.R. 163, MIT Media Lab, Vision and Modeling Group (February 1991)
Bergen, J.R., Anandan, P., Hanna, K., Hingorani, R.: Hierarchical Model-Based Motion Estimation. In: Sandini, G. (ed.) ECCV 1992. LNCS, vol. 588, pp. 237–252. Springer, Heidelberg (1992)
Adelson, E.H., Wang, J.Y.A.: Representing moving images with layers. IEEE Transactions on Image Processing (September 1994)
Peleg, S., Irani, M.: Motion analysis for image enhancement: Resolution, occlusion and transparency. Journal of Visual Communication and Image Representation 4(4), 324–335 (1993)
Black, M.: Combining intensity and motion for incremental segmentation and tracking over long image sequences. In: ECCV (1992)
Bhute, A.N., Meshram, B.B.: IVSS: Integration of Color Feature Extraction Techniques for Intelligent Video Search Systems. In: Proceeding of Int’l Conf. ICECT, Kanyakumari, India (April 2012)
Zhuang, Y., Rui, Y., Huang, T.S., Mehrotra, S.: Adaptive key frame extraction using unsupervised clustering. In: Proc. IEEE Int. Conf. on Image Proc. (1998)
Wu, J., Wei, Z., Chang, Y.: Color and Texture Feature For Content Based Image Retrieval. International Journal of Digital Content Technology and its Applications 4(3) (June 2010)
Oraintara, S., Nguyen, T.T.: Using Phase and Magnitude Information of the Complex directional Filter Bank for Texture Image Retrieval. In: Proc. IEEE Int. Conf. on Image Processing, vol. 4, pp. 61–64 (October 2007)
De Valois, R.L., De Valois, K.K.: A multi-stage color model. Vision Research 33(8), 1053–1065 (1993)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd edn. Addison-Wesley, Reading (1992)
Wang, S.: A Robust CBIR Approach Using Local Color Histograms. Technical report, Department of computer science, University of Alberta, Canada (2001)
Smith, J., Chang, S.: Tools and techniques for color image retrieval. In: Proc. of the SPIE Conference on the Storage and Retrieval for Image and Video Databases IV, San Jose, CA, USA, pp. 426–437 (1996)
Stricker, M.A., Dimai, A.: Color indexing with weak spatial constraints. In: Proc. of the SPIE Conference on the Storage and Retrieval for Image and Video Databases IV, San Diego, CA, USA, pp. 29–40 (February 1996)
Hsu, W., Chua, T.S., Pung, H.K.: An integrated color-spatial approach to content-based imageretrieval. In: Proc. of the ACM Multimedia 1995, pp. 305–313 (1995)
Stricker, M.A., Orengo, M.: Similarity of Color Images. In: Storage and Retrieval for Image and Video Databases III, pp. 381–392 (1995)
Pass, G., Zabih, R.: Histogram Refinement for Content-Based Image Retrieval. In: IEEE Workshop on Applications of Computer Vision, pp. 96–102 (1996)
Han, J., Ma, K.: Fuzzy Color Histogram and Its Use in Color Image Retrieval. IEEE Trans. on Image Processing 11, 944–952 (2002)
Shanmugam, T.N., Rajendran, P.: An Enhanced Content-Based Video Retrieval System based on query clip. International Journal of Research and Reviews in Applied Sciences (December 2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Daga, B. (2013). Content Based Video Retrieval Using Color Feature: An Integration Approach. In: Unnikrishnan, S., Surve, S., Bhoir, D. (eds) Advances in Computing, Communication, and Control. ICAC3 2013. Communications in Computer and Information Science, vol 361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36321-4_57
Download citation
DOI: https://doi.org/10.1007/978-3-642-36321-4_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36320-7
Online ISBN: 978-3-642-36321-4
eBook Packages: Computer ScienceComputer Science (R0)