Abstract
To feature points description of color image, the fact that image color information has some effects on features of image is taken into consideration in this paper. And there is a novel method of SURF (speed up robust features) feature description of color image based on Gaussian color invariance model presented in this paper. During the stage of image feature description, the three kinds of color information in original color image are expressed by three components of Gaussian color invariance model respectively. Then, the matrix consisting of color invariants which are presented by Gaussian color invariance model represents original color image. Hereafter, the method of SURF feature description is used for describing the distribution of feature points. Finally, through our experiences, the correct matching ratio of feature point pairs of our method is higher than some typical algorithms represented in resent years when the image appears affine and blurring transformation.
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Acknowledgements
This work is supported by National Science Foundation of China (No. 61170161, No. 61300155, No. 61503219), Outstanding Young Scientists Foundations Grant of Shandong Province (No. BS2014DX016), Ph.D. Programs Foundation of Ludong University (No. LY2014033, LY2015033). This work is partially supported by NSFC Grants (61503219).
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Sun, W., Shen, Q., Liu, C. (2016). SURF Feature Description of Color Image Based on Gaussian Model. In: Li, K., Li, J., Liu, Y., Castiglione, A. (eds) Computational Intelligence and Intelligent Systems. ISICA 2015. Communications in Computer and Information Science, vol 575. Springer, Singapore. https://doi.org/10.1007/978-981-10-0356-1_28
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DOI: https://doi.org/10.1007/978-981-10-0356-1_28
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