Paper
20 November 2014 An internal self-similarities matching algorithm for IR/visual images based on shape
Xiaoqian Zhang, Yawei Yang, Zhongmin Zhang, Yonghong Du
Author Affiliations +
Proceedings Volume 9300, International Symposium on Optoelectronic Technology and Application 2014: Infrared Technology and Applications; 93001V (2014) https://doi.org/10.1117/12.2072640
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China
Abstract
We present an efficient approach for measuring similarity between visual and IR images based on matching internal self-similarities. What is correlated across images is the internal layout of local self-similarities, even though geometric distortions and at multiple scales. These internal self-similarities are efficiently captured by a compact local "self-similarity descriptor". We compare our measure to commonly used SURF. Experimental results show that the proposed algorithm can realize the rotation invariance, scale invariance and robustness for occlusion. The proposed algorithm can match the shape in the IR and visible images efficiently and correctly.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaoqian Zhang, Yawei Yang, Zhongmin Zhang, and Yonghong Du "An internal self-similarities matching algorithm for IR/visual images based on shape", Proc. SPIE 9300, International Symposium on Optoelectronic Technology and Application 2014: Infrared Technology and Applications, 93001V (20 November 2014); https://doi.org/10.1117/12.2072640
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KEYWORDS
Image registration

Feature extraction

Infrared imaging

Video

Visualization

Heart

Object recognition

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