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Article
Publication date: 6 May 2014

Yong-Hwan Lee, Hyochang Ahn, Han-Jin Cho and June-Hwan Lee

This paper holds a big advantage to enable to recognize faces, regardless of time and place. Also this provides an independent performance of smart phone, because of its…

Abstract

Purpose

This paper holds a big advantage to enable to recognize faces, regardless of time and place. Also this provides an independent performance of smart phone, because of its process by a computer of third party not by that of the mobile device. In addition, it is desirable to minimize the expensive operations in mobile device with constraint computational power (i.e. battery consumption). Thus, the authors exclude the process of transmission failed from the input device. The paper aims to discuss these issues.

Design/methodology/approach

In this paper, the authors have proposed a new face detection and verification algorithm, based on skin color detection to enable extracting the face region from color images of the mobile phone. And then extracted the facial feature as eigenface, verified whether or not the identity of users is right, applied support vector machine to the region of detected face.

Findings

The experimental results for two datasets show that the proposed method achieves slightly higher efficiencies at the detection and verification of user identity, compared with other method, where varying lighting conditions with complex backgrounds, according to be fast and accurate than any other previous methods.

Originality/value

The proposed algorithm enables to implement fast and accurate search using triangle-square transformation for detection of human faces in a digital still color images, obtained by the mobile device camera under unconstraint environments, using advanced skin color model and characteristic points in a detected face.

Details

Journal of Systems and Information Technology, vol. 16 no. 2
Type: Research Article
ISSN: 1328-7265

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Article
Publication date: 9 March 2015

Eunhwa Jung and Kyungho Hong

This study aims at a biometric verification based on facial profile images for mobile security. The modern technology of mobile Internet devices and smart phones such as…

Abstract

Purpose

This study aims at a biometric verification based on facial profile images for mobile security. The modern technology of mobile Internet devices and smart phones such as the iPhone series and Galaxy phone series has revealed the development of information technology of input and output devices as high-definition multimedia interface. The development of information technology requires novel biometric verification for personal identification or authentication in mobile security, especially in Internet banking and mobile Internet access. Our study deals with a biometric verification based on facial profile images for mobile security.

Design/methodology/approach

The product of cellphones with built-in cameras gives us the opportunity of the biometric verification to recognize faces, fingerprints and biological features without any other special devices. Our study focuses on recognizing the left and right facial profile images as well as the front facial images as a biometric verification of personal identification and authentication for mobile security, which can be captured by smart phone devices such as iPhone 4 and Galaxy S2.

Findings

As the recognition technique of the facial profile images for a biometric verification in mobile security is a very simple, relatively easy to use and inexpensive, it can be easily applied to personal mobile phone identification and authentication instead of passwords, keys or other methods. The biometric system can also be used as one of multiple verification techniques for personal recognition in a multimodal biometric system. Our experimental data are taken from persons of all ages, ranging from children to senior citizens.

Originality/value

As the recognition technique of the facial profile images for a biometric verification in mobile security is very simple, relatively easy to use and inexpensive, it can be easily applied to personal mobile phone identification and authentication instead of passwords, keys or other methods. The biometric system can also be used as one of multiple verification techniques for personal recognition in a multimodal biometric system. Our experimental data are taken from persons of all ages, ranging from children to senior citizens.

Details

Journal of Systems and Information Technology, vol. 17 no. 1
Type: Research Article
ISSN: 1328-7265

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Article
Publication date: 1 August 2019

Ziaul Haque Choudhury and M. Munir Ahamed Rabbani

Nowadays, the use of forged e-passport is increasing, which is threatening national security. It is important to improve the national security against international crime…

Abstract

Purpose

Nowadays, the use of forged e-passport is increasing, which is threatening national security. It is important to improve the national security against international crime or terrorism. There is a weak verification process caused by lack of identification processes such as a physical check, biometric check and electronic check. The e-passport can prevent the passport cloning or forging resulting from the illegal immigration. The paper aims to discuss these issues.

Design/methodology/approach

This paper focuses on face recognition to improve the biometric authentication for an e-passport, and it also introduces facial permanent mark detection from the makeup or cosmetic-applied faces, twins and similar faces. An algorithm is proposed to detect the cosmetic-applied facial permanent marks such as mole, freckle, birthmark and pockmark. Active Shape Model into Active Appearance Model using Principal Component Analysis is applied to detect the facial landmarks. Facial permanent marks are detected by applying the Canny edge detector and Gradient Field Histogram of Oriented Gradient.

Findings

This paper demonstrated an algorithm and proposed facial marks detection from cosmetic or makeup-applied faces for a secure biometric passport in the field of personal identification for national security. It also presented to detect and identify identical twins and similar faces. This paper presented facial marks detection from the cosmetic-applied face, which can be mixed with traditional methods. However, the use of the proposed technique faced some challenges due to the use of cosmetic. The combinations of the algorithm for facial mark recognition matching with classical methods were able to attain lower errors in this proposed experiment.

Originality/value

The proposed method will enhance the national security and it will improve the biometric authentication for the e-passport. The proposed algorithm is capable of identifying facial marks from cosmetic-applied faces accurately, with less false positives. The proposed technique shows the best results.

Details

International Journal of Intelligent Unmanned Systems, vol. 8 no. 1
Type: Research Article
ISSN: 2049-6427

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Article
Publication date: 6 September 2018

Ihab Zaqout and Mones Al-Hanjori

The face recognition problem has a long history and a significant practical perspective and one of the practical applications of the theory of pattern recognition, to…

Abstract

Purpose

The face recognition problem has a long history and a significant practical perspective and one of the practical applications of the theory of pattern recognition, to automatically localize the face in the image and, if necessary, identify the person in the face. Interests in the procedures underlying the process of localization and individual’s recognition are quite significant in connection with the variety of their practical application in such areas as security systems, verification, forensic expertise, teleconferences, computer games, etc. This paper aims to recognize facial images efficiently. An averaged-feature based technique is proposed to reduce the dimensions of the multi-expression facial features. The classifier model is generated using a supervised learning algorithm called a back-propagation neural network (BPNN), implemented on a MatLab R2017. The recognition rate and accuracy of the proposed methodology is comparable with other methods such as the principle component analysis and linear discriminant analysis with the same data set. In total, 150 faces subjects are selected from the Olivetti Research Laboratory (ORL) data set, resulting 95.6 and 85 per cent recognition rate and accuracy, respectively, and 165 faces subjects from the Yale data set, resulting 95.5 and 84.4 per cent recognition rate and accuracy, respectively.

Design/methodology/approach

Averaged-feature based approach (dimension reduction) and BPNN (generate supervised classifier).

Findings

The recognition rate is 95.6 per cent and recognition accuracy is 85 per cent for the ORL data set, whereas the recognition rate is 95.5 per cent and recognition accuracy is 84.4 per cent for the Yale data set.

Originality/value

Averaged-feature based method.

Details

Information and Learning Science, vol. 119 no. 9/10
Type: Research Article
ISSN: 2398-5348

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Article
Publication date: 14 May 2020

Minghua Wei

In order to solve the problem that the performance of the existing local feature descriptors in uncontrolled environment is greatly affected by illumination, background…

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Abstract

Purpose

In order to solve the problem that the performance of the existing local feature descriptors in uncontrolled environment is greatly affected by illumination, background, occlusion and other factors, we propose a novel face recognition algorithm in uncontrolled environment which combines the block central symmetry local binary pattern (CS-LBP) and deep residual network (DRN) model.

Design/methodology/approach

The algorithm first extracts the block CSP-LBP features of the face image, then incorporates the extracted features into the DRN model, and gives the face recognition results by using a well-trained DRN model. The features obtained by the proposed algorithm have the characteristics of both local texture features and deep features that robust to illumination.

Findings

Compared with the direct usage of the original image, the usage of local texture features of the image as the input of DRN model significantly improves the computation efficiency. Experimental results on the face datasets of FERET, YALE-B and CMU-PIE have shown that the recognition rate of the proposed algorithm is significantly higher than that of other compared algorithms.

Originality/value

The proposed algorithm fundamentally solves the problem of face identity recognition in uncontrolled environment, and it is particularly robust to the change of illumination, which proves its superiority.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 13 no. 2
Type: Research Article
ISSN: 1756-378X

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Article
Publication date: 19 June 2017

Yang Xin, Yi Liu, Zhi Liu, Xuemei Zhu, Lingshuang Kong, Dongmei Wei, Wei Jiang and Jun Chang

Biometric systems are widely used for face recognition. They have rapidly developed in recent years. Compared with other approaches, such as fingerprint recognition

Abstract

Purpose

Biometric systems are widely used for face recognition. They have rapidly developed in recent years. Compared with other approaches, such as fingerprint recognition, handwriting verification and retinal and iris scanning, face recognition is more straightforward, user friendly and extensively used. The aforementioned approaches, including face recognition, are vulnerable to malicious attacks by impostors; in such cases, face liveness detection comes in handy to ensure both accuracy and robustness. Liveness is an important feature that reflects physiological signs and differentiates artificial from real biometric traits. This paper aims to provide a simple path for the future development of more robust and accurate liveness detection approaches.

Design/methodology/approach

This paper discusses about introduction to the face biometric system, liveness detection in face recognition system and comparisons between the different discussed works of existing measures.

Originality/value

This paper presents an overview, comparison and discussion of proposed face liveness detection methods to provide a reference for the future development of more robust and accurate liveness detection approaches.

Details

Sensor Review, vol. 37 no. 3
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 3 October 2019

Dinesh Kumar D.S. and P.V. Rao

The purpose of this paper is to incorporate a multimodal biometric system, which plays a major role in improving the accuracy and reducing FAR and FRR performance metrics…

Abstract

Purpose

The purpose of this paper is to incorporate a multimodal biometric system, which plays a major role in improving the accuracy and reducing FAR and FRR performance metrics. Biometrics plays a major role in several areas including military applications because of robustness of the system. Speech and face data are considered as key elements that are commonly used for multimodal biometric applications, as they are simultaneously acquired from camera and microphone.

Design/methodology/approach

In this proposed work, Viola‒Jones algorithm is used for face detection, and Local Binary Pattern consists of texture operators that perform thresholding operation to extract the features of face. Mel-frequency cepstral coefficients exploit the performances of voice data, and median filter is used for removing noise. KNN classifier is used for fusion of both face and voice. The proposed method produces better results in noisy environment with better accuracy. In this proposed method, from the database, 120 face and voice samples are trained and tested with simulation results using MATLAB tool that improves performance in better recognition and accuracy.

Findings

The algorithms perform better for both face and voice recognition. The outcome of this work provides better accuracy up to 98 per cent with reduced FAR of 0.5 per cent and FRR of 0.75 per cent.

Originality/value

The algorithms perform better for both face and voice recognition. The outcome of this work provides better accuracy up to 98 per cent with reduced FAR of 0.5 per cent and FRR of 0.75 per cent.

Details

International Journal of Intelligent Unmanned Systems, vol. 8 no. 1
Type: Research Article
ISSN: 2049-6427

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Article
Publication date: 6 December 2017

Fabio Bacchini and Ludovica Lorusso

This study aims to explore the ethical and social issues of tattoo recognition technology (TRT) and tattoo similarity detection technology (TSDT), which are expected to be…

Abstract

Purpose

This study aims to explore the ethical and social issues of tattoo recognition technology (TRT) and tattoo similarity detection technology (TSDT), which are expected to be increasingly used by state and local police departments and law enforcement agencies.

Design/methodology/approach

The paper investigates the new ethical concerns raised by tattoo-based biometrics on a comparative basis with face-recognition biometrics.

Findings

TRT raises much more ethically sensitive issues than face recognition, because tattoos are meaningful biometric traits, and tattoo identification is tantamount to the identification of many more personal features that normally would have remained invisible. TSDT’s assumption that classifying people in virtue of their visible features is useful to foretell their attitudes and behaviours is dangerously similar to racist thought.

Practical implications

The findings hope to promote an active debate on the ethical and social aspects of tattoo-based biometrics before it is intensely implemented by law enforcement agencies.

Social implications

Tattooed individuals – inasmuch as they are more controlled and monitored – are negatively discriminated in comparison to un-tattooed individuals. As tattooing is not uniformly distributed among population, many demographic groups like African–Americans will be overrepresented in tattoos databases used by TRT and TSDT, thus being affected by disproportionately higher risk to be found as a match for a given suspect.

Originality/value

TRT and TSDT represent one of the new frontiers of biometrics. The ethical and social issues raised by TRT and TSDT are currently unexplored.

Details

Journal of Information, Communication and Ethics in Society, vol. 16 no. 2
Type: Research Article
ISSN: 1477-996X

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Article
Publication date: 1 January 2006

Christine Connolly

Reports on the work of the National Physical Laboratory in evaluating commercial biometric authentification systems.

Abstract

Purpose

Reports on the work of the National Physical Laboratory in evaluating commercial biometric authentification systems.

Design/methodology/approach

Reviews the results of the first round of testing, completed in 2000, and describes the new equipment to be used in the second round.

Findings

Various biometric features are being used for the unique identification of individual people, but so far the iris seems to be the most stable and is most successfully encoded for rapid and accurate recognition. Many biometric systems have an adjustable threshold controlling the trade‐off between security and user‐friendliness. By combining biometric features, for example, the geometry and texture of the face, the accuracy may be improved.

Originality/value

Reports on the standardization of test procedures for evaluating biometric devices, and the availability of objective evaluation results for different types of equipment.

Details

Sensor Review, vol. 26 no. 1
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 1 March 2001

Ihsan Faraj

In features based design systems that are underpinned by solid models, buildings are designed by applying features to the design domain. A feature may be translated and/or…

Abstract

In features based design systems that are underpinned by solid models, buildings are designed by applying features to the design domain. A feature may be translated and/or rotated in order to position it in the desired place. Contradiction between the applied features and resulting features may occur due to the features interaction, wrong positioning, or inadequate parameters supplied by the user during the product definition. Moreover, the application of other features may cause some features to degenerate to further features. Therefore, verification of the resulting features must be performed against the applied features to establish whether the resulting features conform to the underlying geometry. Current feature‐based design systems employ a mechanism of tagging feature labels onto geometry. This approach does not guarantee the geometric correctness of the resultant feature and knowledge of the topology of the resulting feature and a geometric analysis is necessary to correctly identify the validity of the resultant feature. The research reported in this paper proposes an alternative approach which uses a product model that permits all geometrical and technological information associated with the design and construction stages to be represented. Individual features can be extracted from the product model and analysed to determine their accessibility. Methods which use the product description and other construction data to determine feature validity, accessibility and machinability are used. Each volumetric feature corresponds to a solid that can be added by one or more construction process or removed by one or more machining operations; as a consequence of applying volumetric features, surface features are generated. These surface features provide enough information to enable the accessibility, and machinability of the individual features to be determined and establish the possible routes in which the feature can be accessed if any.

Details

Construction Innovation, vol. 1 no. 1
Type: Research Article
ISSN: 1471-4175

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