Color Filter Based on Image ROI Extraction

Su Huan Wang; Jian Yin

doi:10.4028/www.scientific.net/AMM.246-247.1121

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 246-247Color Filter Based on Image ROI Extraction

Color Filter Based on Image ROI Extraction

Abstract:

With the rapid development of Internet, more and more enterprises establish business sites to achieve the purpose of online transactions. Taking taobao.com for example, hundreds of millions of goods trade on the trading platform. In front of the huge commodity image database, extraction of image features is very convenient for people to find out images of user requirement. This paper focus mainly on the color feature of images. Firstly, we segment ROI of images using grabCut algorithm; secondly, we extract primary color of images by using dominant color descriptor of MPEG 7; Thirdly, we adopt RGB color quantization to quantize the primary color. Finally achieve the purpose of image color navigation. I have done experiment to compare with some other methods, and find that the algorithms I adopted make a better performance.

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Periodical:

Applied Mechanics and Materials (Volumes 246-247)

Pages:

1121-1124

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.246-247.1121

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Online since:

December 2012

Authors:

Su Huan Wang, Jian Yin

Keywords:

Color Navigation, Dominant Color Descriptor, Grabcut, RGB

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References

[1] Justin F. Talbot, Xiaoqian Xu Abstract_Implementing_GrabCut. pdf.

Google Scholar

[2] BOYKOV, Y., AND JOLLY, M. -P. 2001. Interactive graph cuts for optimal boundary and region segmentation of objects in n-d images. In ICCV, 105–112.

DOI: 10.1109/iccv.2001.937505

Google Scholar

[3] ROTHER, C., KOLMOGOROV, V., AND BLAKE, A. 2004. Grabcut- interactive foreground extraction using iterated graph cuts. Proc. ACM Siggraph.

DOI: 10.1145/1186562.1015720

Google Scholar

[4] Mona Vajihollahi , Roozbeh Farahbod The MPEG 7 Visual Standard for Content Description.

Google Scholar

[5] Jens-Rainer Ohm, Heon Jun Kim, Santhana Krishnamachari, B. S. Manjunath, Dean S. Messing, Akio Yamada. The MPEG-7 Color Descriptors.

Google Scholar

[6] B.S. Manjunath, J. -R. Ohm, V.V. Vasudevan, and A. Yamada, MPEG-7 Color and Texture Descriptors, IEEE Trans. Circuits Syst. Video Technol., vol. 11, pp.703-715, June (2001).

DOI: 10.1109/76.927424

Google Scholar

[7] M. Martinez, Overview of the MPEG-7 Standard, ISO/IEC JTC1/SC29/WG1, (2001).

Google Scholar

[8] BLAKE A, ROTHER C, BROWN M, et al. Interactive image segmentation using an adaptive GMMRF model[EB/OL]. ( 2004- 02- 09).

Google Scholar

[9] Peng Bo, zhang Lei, Yang Jian．Iterated Graph Cuts fDr Image segmentation[c]computer Vision-AccV. [s1]: [s. n. ], 2009: 677-686.

DOI: 10.1007/978-3-642-12304-7_64

Google Scholar