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Open AccessArticle

Multi-Sensor Face Registration Based on Global and Local Structures

1
Hebei Engineering Research Center for Assembly and Inspection Robot, North China Institute of Aerospace Engineering, Langfang 065000, China
2
Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing 100192, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2019, 9(21), 4623; https://doi.org/10.3390/app9214623
Received: 10 September 2019 / Revised: 27 October 2019 / Accepted: 28 October 2019 / Published: 30 October 2019
(This article belongs to the Special Issue Intelligent Processing on Image and Optical Information)
The work reported in this paper aims at utilizing the global geometrical relationship and local shape feature to register multi-spectral images for fusion-based face recognition. We first propose a multi-spectral face images registration method based on both global and local structures of feature point sets. In order to combine the global geometrical relationship and local shape feature in a new Student’s t Mixture probabilistic model framework. On the one hand, we use inner-distance shape context as the local shape descriptors of feature point sets. On the other hand, we formulate the feature point sets registration of the multi-spectral face images as the Student’s t Mixture probabilistic model estimation, and local shape descriptors are used to replace the mixing proportions of the prior Student’s t Mixture Model. Furthermore, in order to improve the anti-interference performance of face recognition techniques, a guided filtering and gradient preserving image fusion strategy is used to fuse the registered multi-spectral face image. It can make the multi-spectral fusion image hold more apparent details of the visible image and thermal radiation information of the infrared image. Subjective and objective registration experiments are conducted with manual selected landmarks and real multi-spectral face images. The qualitative and quantitative comparisons with the state-of-the-art methods demonstrate the accuracy and robustness of our proposed method in solving the multi-spectral face image registration problem. View Full-Text
Keywords: multi-sensor; face registration; inner-distance; Student’s-t Mixtures Model; image fusion multi-sensor; face registration; inner-distance; Student’s-t Mixtures Model; image fusion
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MDPI and ACS Style

Li, W.; Dong, M.; Lu, N.; Lou, X.; Zhou, W. Multi-Sensor Face Registration Based on Global and Local Structures. Appl. Sci. 2019, 9, 4623.

AMA Style

Li W, Dong M, Lu N, Lou X, Zhou W. Multi-Sensor Face Registration Based on Global and Local Structures. Applied Sciences. 2019; 9(21):4623.

Chicago/Turabian Style

Li, Wei; Dong, Mingli; Lu, Naiguang; Lou, Xiaoping; Zhou, Wanyong. 2019. "Multi-Sensor Face Registration Based on Global and Local Structures" Appl. Sci. 9, no. 21: 4623.

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