一种新的结合环状区域划分的特征描述子

doi:10.3969/j.issn.1001-2400.2016.02.012

Abstract

Abstract:

A novel regional image feature description method is proposed to improve the affine invariant and matching performance of image feature descriptors. Firstly, the Hessian-affine detector is adopted to extract the image feature region,which is normalized to the unit circular feature region to meet the affine invariant requirement. Secondly, in order to avoid the error caused by calculating main gradient orientation on the histogram, the annular-based region division is proposed on the local coordinate system of the image sample point to calculate the local gradient orientation. Experimental results demonstrate that the new method not only has an excellent affine invariant,but also is significantly better than the SIFT descriptor in match performance.

Key words: computer vision, local feature, affine invariant, local coordinate

CLC Number:

TP391

LI Jianbing;XIAO Xiao;LI Xiaoping;HOU Xiaoli. Local coordinate gradient descriptor based on cyclic division[J].Journal of Xidian University, 2016, 43(2): 64-69.

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Local coordinate gradient descriptor based on cyclic division

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