Forthcoming articles


International Journal of Biometrics


These articles have been peer-reviewed and accepted for publication in IJBM, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.


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International Journal of Biometrics (5 papers in press)


Regular Issues


  • Recognition of Ear based on Partial Features Fusion   Order a copy of this article
    by Vidyasri Ramesh, Priyalakshmi B, Ravi Raja M, Priyanka S 
    Abstract: Multi biometric systems like face and ear recognition techniques are adopted for the forensic and civilian applications to address the challenges of the facial expressions and occlusions. Numerous face and ear techniques have been proposed so far. Yet it becomes difficult to remove occlusions in ear. Ear occlusions can be of various forms such as, cap, hair, scarf, earrings, etc. Due to occlusion during Identification stage recognition will certainly cause the loss of Information. In this paper, an Occlusion detection of Ear that will recognize the occlusion information during the Identification stage and by using fusion method, the matching of the samples are processed.
    Keywords: Ear recognition; occlusion estimation; biometric system; FLDA feature extraction; borda count; rank features.

  • Face Analysis in Video : Face Detection and Tracking with Pose Estimation   Order a copy of this article
    by Hazar Mliki, Mohamed Hammami 
    Abstract: We introduced a full automatic approach to achieve face detection and tracking with pose estimation in video sequences. The proposed approach consists of three modules: face detection module, face tracking module and face pose estimation module. A combination between detection and tracking modules was performed to overcome the different challenging problems that might occur while detecting or tracking faces. Afterward face pose estimation module was applied to select the best camera capture which is closest to the frontal face view for better face recognition task. The performance of these modules was evaluated with an experimental study which has proven the robustness of the proposed approach for a face analysis in video.
    Keywords: Face Detection; Face Tracking; Face Pose Estimation; Data-Mining; SVM; Adaboost.

  • Biometric security system: A rigorous review of Unimodal and Multimodal Biometrics Techniques   Order a copy of this article
    by Ujwalla Gawande, Yogesh Golhar 
    Abstract: Biometric based system is used for authentication of an individual and to counter the possible threats used for security purpose. A wide variety of systems require reliable authentication schemes to either confirm or determine the identity of individuals. The purpose of such schemes is to ensure that the services are accessed by the legitimate user. With growing concerns about terrorist activities, security breaches,financial fraud, biometric based person identification is the need of today. This paper focuses on the latest work carried out in the area of unimodal and multimodal biometric system. Many researchers developed biometric based system despite of that each system has its own limitations. This paper gives qualitative and computational analysis of existing biometric system and describe various unimodal and multimodal systems. The main aim is to provide a comparative and informative study of existing methods and provide probable solutions of challenges with appropriate justification.
    Keywords: Multimodal biometrics; unimodal biometrics; feature fusion; classification; identification; recognition; texture; error rate; neural network; biometric system.

  • New Face Expression Recognition using Polar Angular Radial Transform and Principal Component Analysis   Order a copy of this article
    by Imene TALEB, Madani Ould Maamar, Abdelaziz Ouamri 
    Abstract: This paper presents a new method for facial expression recognition (FER)using a polar mathematical development based on the radial angular transformation called polar angular radial transform (P -ART) and principal component analysis (PCA).The new ART is a powerful descriptor in terms of robustness and description form and way more information-rich compared to the conventional Cartesian descriptor. Support Vector Machine (SVM) training is utilized to recognize the facial expression for a input face image. Finally, the experimental results show the performance of the P -ART and the PCA. The fusion of these two techniques can be better than other existing methods of recognition of facial expression. During the experiment, the basis of facial given Japanese Female Facial Expression (JAFFE) and the Cohn-Kanade databases has been used.
    Keywords: facial expression recognition (FER); Polar Angular Radial Transform (P -ART) ; Principal Component Analysis (PCA);Support Vector Machine (SVM); Fusion; Japanese Female Expression (JAFFE); Cohn-Kanade.

  • Biometric Authentication System Based on Texture Features of Retinal Images   Order a copy of this article
    by Jarina B. Mazumdar, S.R. Nirmala 
    Abstract: In biometric authentication system, distinct set of characteristic features are used to identify an authorized person. Retina is a stable biometric feature because of its location and unique physiological characteristics. In this paper, we propose a texture feature based retinal authentication system. Texture features are considered as important features for authentication purpose. These texture features of retina are extracted using Local Con guration Pattern (LCP) and Radon transform technique. The LCP computes the local structural information as well as the microscopic information of the image. Using Radon transform on retinal images, Radon features are extracted which contains the texture information of the blood vessels. A feature vector is formed by combining all theses LCP and Radon features and then fed to a Feed-forward Arti cial Neural Network (FANN) classi er. This stage checks whether the test image belongs to the authorized person or not. Three general retinal databases DRIVE, HRF, Messidor, and images collected from two local eye hospitals are considered to authenticate a person. Two retinal authentication databases RIDB and VARIA are also used for evaluating the performance of the system. The results obtained show that the system is effective and efficient in authenticating the individuals.
    Keywords: Texture feature; LCP; Radon transform; FANN.