PalmNet: Gabor-PCA Convolutional Networks for Touchless Palmprint Recognition
نویسندگان
چکیده
منابع مشابه
Palmprint Recognition Using PCA and Weighted Feature Level Fusion of 2D–Gabor and Log-Gabor Features
Palmprint biometric technology is most accurate and reliable, which has acquired good impact over the remaining biometric technologies. Palmprint contains various features like minutiae points, wrinkles, palm lines and texture, etc. A Number of line based approaches, subspace based approaches and texture based methods for extracting features from Palmprint have been considered and studied thoro...
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Palmprint recognition, as a new branch of biometric technology, has attracted much attention in recent years. Various palmprint representations have been proposed for recognition. Gabor feature has been recognized as one of the most effective representations for palmprint recognition, where Gabor phase and orientation feature representations are extensively studied. In this paper, we explore a ...
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متن کاملGabor Convolutional Networks
Steerable properties dominate the design of traditional filters, e.g., Gabor filters, and endow features the capability of dealing with spatial transformations. However, such excellent properties have not been well explored in the popular deep convolutional neural networks (DCNNs). In this paper, we propose a new deep model, termed Gabor Convolutional Networks (GCNs or Gabor CNNs), which incorp...
متن کاملPalmprint Recognition with PCA and ICA
Palmprint is one of the relatively new physiological biometrics due to its stable and unique characteristics. The rich texture information of palmprint offers one of the powerful means in personal recognition. According to psycho-physiology study, the primary visual cortex in the visual area of human brain is responsible for creating the basis of a three-dimensional map of visual space, and ext...
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ژورنال
عنوان ژورنال: IEEE Transactions on Information Forensics and Security
سال: 2019
ISSN: 1556-6013,1556-6021
DOI: 10.1109/tifs.2019.2911165