Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artifici...Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.展开更多
This study proposes a new model of granary storage weight detection based on the Janssen model to satisfy the strategic requirements of granary storage quantity detection in China. The model theoretically elucidates t...This study proposes a new model of granary storage weight detection based on the Janssen model to satisfy the strategic requirements of granary storage quantity detection in China. The model theoretically elucidates the relationship between granary storage weight and bottom/side pressure. A new layout of pressure sensors along the inner and outer rings is also proposed to obtain the pressure value. The experimental results indicate that the detection error of the proposed model is significantly lower than 1% with respect to the low-cost detection system, and this effectively satisfies the actual requirement for real-time monitoring of granary storage quantity.展开更多
基金supported by the NSFC (U1536206,61232016,U1405254,61373133, 61502242)BK20150925the PAPD fund
文摘Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.
基金Supported by Natural Science Project of Henan Provincial Science and Technology Department(172106000013)State Key Laboratory of Grain Information Processing and Control,Ministry of Education(KFJJ-2016-102)Grain Information Processing Technology of University Science and Technology Innovation Team in Henan Province(16IRTSTHN026)
文摘This study proposes a new model of granary storage weight detection based on the Janssen model to satisfy the strategic requirements of granary storage quantity detection in China. The model theoretically elucidates the relationship between granary storage weight and bottom/side pressure. A new layout of pressure sensors along the inner and outer rings is also proposed to obtain the pressure value. The experimental results indicate that the detection error of the proposed model is significantly lower than 1% with respect to the low-cost detection system, and this effectively satisfies the actual requirement for real-time monitoring of granary storage quantity.
