Performance evaluation of SIFT under low light contrast

Hao Wang; Songzhi Jin; Xiaodan Wei; Cong Zhang; Ruiguang Hu

doi:10.1117/12.2535592

14 February 2020 Performance evaluation of SIFT under low light contrast

Hao Wang, Songzhi Jin, Xiaodan Wei, Cong Zhang, Ruiguang Hu

Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 1143006 (2020) https://doi.org/10.1117/12.2535592
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

As an excellent method for extracting distinctive invariant features from images, SIFT (scale-invariant feature transform) can effectively resist affine transformation such as translation and rotation of images, and theoretically has better resistance to illumination changes ^[1]. However, in practical applications the performance of SIFT is always affected by the contrast reduction caused by illumination changes. In this paper, the performance of SIFT under different contrasts is systematically analyzed and evaluated, and a reasonable explanation is given for the reason of SIFT performance change under different illumination conditions. And a SIFT fast matching method based on contrast compression is proposed.

Citation Download Citation

Hao Wang, Songzhi Jin, Xiaodan Wei, Cong Zhang, and Ruiguang Hu "Performance evaluation of SIFT under low light contrast", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 1143006 (14 February 2020); https://doi.org/10.1117/12.2535592

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