Acta Optica Sinica, Volume. 39, Issue 7, 0710001(2019)
Multispectral Face Image Registration Based on T-Distribution Mixture Model
Fig. 1. Infrared and visible face image registration process based on feature maps
Fig. 2. Diagrams of face silhouette feature extraction based on IDSC. (a) Bellman-Ford shortest path graph built using face silhouette landmark points; (b) four marked points; (c) their IDSC feature histograms
Fig. 5. Registration results on synthetic Chinese character point sets. (a)-(c) Point sets before registration; (d)-(f) registration results of proposed algorithm; (g)-(i) recall curves of three registration algorithms
Fig. 6. Visible and infrared face registration results in UTK-IRIS database. (a)(b) Original visible and infrared images; (c) face edge maps; (d)(e) checkerboards of warping visible image into and infrared image
Fig. 7. Quantitative result comparison of multispectral face image pairs of different individuals. (a) Charles; (b) Heo; (c) Gribok; (d) Sharon
Fig. 8. Visible and infrared face image registration and fusion results captured by ourselves. (a) Original visible images; (b) original infrared images; (c) checkerboard images; (d) fusion images
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Wei Li, Mingli Dong, Naiguang Lü, Xiaoping Lou. Multispectral Face Image Registration Based on T-Distribution Mixture Model[J]. Acta Optica Sinica, 2019, 39(7): 0710001
Category: Image Processing
Received: Jan. 7, 2019
Accepted: Apr. 1, 2019
Published Online: Jul. 16, 2019
The Author Email: Dong Mingli (dongml@bistu.edu.cn)