Multi-features association-based local HOG description for image matching

Bingbing Wu; Shilin Zhou; Lin Lei; Kefeng Ji

doi:10.1117/12.2209096

14 December 2015 Multi-features association-based local HOG description for image matching

Bingbing Wu, Shilin Zhou, Lin Lei, Kefeng Ji

Proceedings Volume 9813, MIPPR 2015: Pattern Recognition and Computer Vision; 981311 (2015) https://doi.org/10.1117/12.2209096
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China

Abstract

Image matching has always been a very important research areas in computer vision. The performance will directly affect the matching results. Among local descriptors, the Scale Invariant Feature Transform(SIFT) is a milestone in image matching, while HOG as an excellent descriptor is widely used in 2D object detection, but it seldom used as a descriptor for matching. In this article, we suppose to pool these algorithms and we use a simple modification of the Rotation- Invariant HOG(RI-HOG) to describe the feature domain detected by SIFT. The RI-HOG is Fourier analyzed in the polar/spherical coordinates. Later in our experiment, we test the performance of our method on a datasets. We are surprised to find that the method outperforms other descriptors in image matching in accuracy.

Citation Download Citation

Bingbing Wu, Shilin Zhou, Lin Lei, and Kefeng Ji "Multi-features association-based local HOG description for image matching", Proc. SPIE 9813, MIPPR 2015: Pattern Recognition and Computer Vision, 981311 (14 December 2015); https://doi.org/10.1117/12.2209096

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