Entropy-Based Face Recognition and Spoof Detection for Security Applications

Pujol, Francisco A.; Rizo-Maestre, Carlos; López, Mar Pujol

doi:10.3390/su12010085

Cited by 15 publications

(9 citation statements)

References 62 publications

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“…Information entropy is derived from information theory [ 33 ], which was originally applied to assess the uncertainty of hydrological models [ 34 ]. The experiments show that the entropy information significantly improves the recognition rate and the robustness of the algorithm [ 35 ]. Analyzing the coordination relationship between economic development and investment potential with methods such as the entropy weight method, etc.…”

Section: Literature Review and Methodologymentioning

confidence: 99%

A Novel Multi-Criteria Decision-Making Model for Building Material Supplier Selection Based on Entropy-AHP Weighted TOPSIS

Chen

2020

Entropy

160

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The type of criterion weight can be distinguished according to different decision methods. Subjective weights are given by decision makers based on their knowledge, experience, expertise, and other factors. Objective weights are obtained through multi-step calculations of the evaluation matrix constructed from the actual information about the evaluation criteria of the alternatives. A single consideration of these two types of weights often results in biased results. In addition, in order to build an effective supply chain source, buyers must find suitable quality products and/or service providers in the process of supplier selection. Based on the above reasons, it is difficult to accurately select the appropriate alternative. The main contribution of this paper is to combine entropy weight, analytic hierarchy process (AHP) weight, and the technique for order preference by similarity to an ideal solution (TOPSIS) method into a suitable multi-criteria decision making (MCDM) solution. The TOPSIS method is extended with entropy-AHP weights, and entropy-AHP weights are used instead of subjective weights. A novel decision-making model of TOPSIS integrated entropy-AHP weights is proposed to select the appropriate supplier. Finally, we take the selection of building material suppliers as an example and use sensitivity analysis to show that the combination of the TOPSIS method based on entropy-AHP weights can effectively select the appropriate supplier.

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Section: Literature Review and Methodologymentioning

confidence: 99%

A Novel Multi-Criteria Decision-Making Model for Building Material Supplier Selection Based on Entropy-AHP Weighted TOPSIS

Chen

2020

Entropy

160

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“…Information entropy originates from information theory [ 34 ], which was initially used to evaluate the uncertainty of hydrological models [ 35 ]. The experimental results show that entropy information can significantly improve the robustness and recognition rate of the algorithm [ 36 ]. A research is based on TOPSIS technology and uses entropy weight information to calculate the weight of the criteria, in order to selecting suitable suppliers in a green environment [ 37 ].…”

Section: Literature Review and Methodologymentioning

confidence: 99%

A Hybrid Multi-Criteria Decision-Making Approach Based on ANP-Entropy TOPSIS for Building Materials Supplier Selection

Chen¹

2021

Entropy

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This article will tell you how to combine “entropy” in the model to reduce the bias of multi-criteria evaluation. Subjective weights are usually determined by decision makers based on their professional background, experience and knowledge, and other factors. The objective weight is obtained by constructing an evaluation matrix of the information based on the actual information of the evaluation criteria of the scheme, and obtained through multi-step calculations. Different decision-making methods are based on different weight types. Considering only one of the two weights often leads to biased results. In addition, in order to establish an effective supply chain, buyers must find suitable merchants among suppliers that provide quality products and/or services. Based on the above factors, it is difficult to choose a suitable alternative. The main contribution of this paper is to combine analytic network process (ANP), entropy weight and the technique for order preference by similarity to an ideal solution (TOPSIS) to construct a suitable multi-criteria decision (MCDM) model. By means of ANP-entropy weights to extend the TOPSIS method, ANP-entropy weights are used to replace subjective weights. A supplier selection decision-making model based on ANP-entropy TOPSIS is proposed. At last, the sensitivity analysis shows that, taking the selection of building materials suppliers as an example, the hybrid ANP-entropy TOPSIS method can effectively select suitable suppliers.

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“…Surinta et al [ 28 ] claimed that, in gender recognition domain, the Histogram of Oriented Gradient (HOG) descriptor outperforms the scale-invariant feature transform (SIFT) descriptor when combined with the support vector machine (SVM). A face recognition system is designed based on the entropy of each face region in HOG descriptor [ 29 ].…”

Section: State Of the Artmentioning

confidence: 99%

Spoofed Facial Presentation Attack Detection by Multivariate Gradient Descriptor in Micro-Expression Region

Karmakar¹,

Mukherjee²,

Datta

2021

Pattern Recognit. Image Anal.

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Facial video presentation is a topic of interest in many security systems due to its non-intrusive nature. However, such systems are vulnerable to spoof attacks made by fake face videos and thereby gaining unauthorized access in the system. For a robust biometric system anti spoofing approaches like liveness detection ought to be implemented in order to counter the aforesaid print and replay attacks. This article proposes a novel approach of anti spoofing using Multivariate histogram of oriented gradients descriptor in the auto detected micro expression (μE) regions of human facial videos. Facial μE are very brief, spontaneous facial expressions that highlight the face of humans when they either unconsciously or deliberately conceal an emotion. The work emphasizes the variations in μE in fake and original video representation by a considerable amount and claims such a variance is a tool to combat against presentation attacks. In particular, the method automatically extracts the ROI of major changes in μE using the Multivariate orientation gradients parameter and thus proposes this descriptor as one of the most suitable tools to characterize the liveness. The entire implementation is carried out on the self-created Database for replay attacks. The result obtained is satisfactory and tested statistically significant.

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Entropy-Based Face Recognition and Spoof Detection for Security Applications

Cited by 15 publications

References 62 publications

A Novel Multi-Criteria Decision-Making Model for Building Material Supplier Selection Based on Entropy-AHP Weighted TOPSIS

A Novel Multi-Criteria Decision-Making Model for Building Material Supplier Selection Based on Entropy-AHP Weighted TOPSIS

A Hybrid Multi-Criteria Decision-Making Approach Based on ANP-Entropy TOPSIS for Building Materials Supplier Selection

Spoofed Facial Presentation Attack Detection by Multivariate Gradient Descriptor in Micro-Expression Region

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