Spatial distribution descriptor-based keypoints matching algorithm

Guanghua Gu; Yao Zhao; Zhenfeng Zhu

doi:10.1117/1.3615651

1 September 2011 Spatial distribution descriptor-based keypoints matching algorithm

Guanghua Gu, Yao Zhao, Zhenfeng Zhu

Author Affiliations +

Funded by: National Natural Science Foundation of China, Natural Science Foundation of China, National Natural Science Funds for Distinguished Young Scholar, National Science Foundation of China for Distinguished Young Scholars, Sino-Singapore JRP, Fundamental Research Funds for the Central Universities, Beijing Natural Science Foundation, and Fundamental Research Funds for the Central Universities

Optical Engineering, Vol. 50, Issue 9, 097001 (September 2011). https://doi.org/10.1117/1.3615651

Abstract

Matching points between two or multiple images of a scene is a vital component in many computer vision and pattern recognition tasks. The key step of point matching is how to construct a distinctive and robust descriptor. A state-of-the-art scale-invariant feature transform (SIFT) descriptor has proven that it outperforms other local descriptors on the distinctiveness and robustness. However, the SIFT descriptor neglects the global context of the feature points, as thus it fails to resolve the ambiguities that occur in local similar regions in an image. In this paper, a spatial distribution (SD) descriptor is constructed for each feature point detected by the SIFT method. It uses a log-polar histogram to build the global component according to the difference-of-Gaussian convolution image information. The spatial distribution descriptor has rotation, zoom invariance and partial skewness invariance due to that it integrates the local and global information of feature points. Points matching are performed on various images by the proposed framework. Experimental results show that the SD method outperforms the method using only SIFT.

©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Guanghua Gu, Yao Zhao, and Zhenfeng Zhu "Spatial distribution descriptor-based keypoints matching algorithm," Optical Engineering 50(9), 097001 (1 September 2011). https://doi.org/10.1117/1.3615651

Published: 1 September 2011

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KEYWORDS

Sensors

Convolution

Optical engineering

Information science

Zoom lenses

Visualization

Computer vision technology

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