2021
DOI: 10.3390/s22010304
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A Novel Infrared and Visible Image Fusion Approach Based on Adversarial Neural Network

Abstract: The presence of fake pictures affects the reliability of visible face images under specific circumstances. This paper presents a novel adversarial neural network designed named as the FTSGAN for infrared and visible image fusion and we utilize FTSGAN model to fuse the face image features of infrared and visible image to improve the effect of face recognition. In FTSGAN model design, the Frobenius norm (F), total variation norm (TV), and structural similarity index measure (SSIM) are employed. The F and TV are … Show more

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Cited by 5 publications
(5 citation statements)
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“…Both of these methods have only been tested on adults and do not necessarily use the fused images for the face detection or the vital sign detection. [55]. They state that the recognition improves when fusing data.…”
Section: Face Detection Using Fused Imagesmentioning
confidence: 99%
See 1 more Smart Citation
“…Both of these methods have only been tested on adults and do not necessarily use the fused images for the face detection or the vital sign detection. [55]. They state that the recognition improves when fusing data.…”
Section: Face Detection Using Fused Imagesmentioning
confidence: 99%
“…Chen et al propose a neural network for creating fusion images for face recognition [ 55 ]. They state that the recognition improves when fusing data.…”
Section: Introductionmentioning
confidence: 99%
“…The use of multiple spectral bands improves the performance of facial recognition system, this explains the interest of researchers on MS facial recognition in recent years [5] [10] [11]. A face recognition system can be represented by four main modules: capture, feature extraction, matching and decision.…”
Section: Related Workmentioning
confidence: 99%
“…Security measures must protect data from change and scrutiny to maintain privacy, dependability, and accessibility [10]. Successful IoT face recognition research has led to many applications [11,12]. Deep learning uses advanced neural networks.…”
Section: Introductionmentioning
confidence: 99%