Volume 11 Issue 4 - October 2018

  • 1. Age invariant face recognition using fuzzy local binary pattern and artificial neural network classifier

    Authors : Ojo John Adedapo, Joseph Oluwaseunoladunni

    Pages : 62-67

    DOI : http://dx.doi.org/10.21172/1.114.11

    Keywords : Fuzzy, Local Binary Pattern, Periocular region, Normalization, Classification

    Abstract :

    Several attempts have been made on Age-Invariant Face Recognition (AIFR), but most available algorithms are based on age estimation and aging simulation, which have several limitations; such as lack of robust identifiable feature that are stable across ages, need for normal illumination and neutral facial expressions. Hence, there is a need for the development of an improved AIFR system that can handle these shortcomings. In this work, an AIFR system using local-feature based approach was developed. It uses Fuzzy Local Binary Pattern (FLBP) algorithm for feature extraction and Artificial Neural Network (ANN) for classification. Face and Gesture Recognition Research Network (FG-NET) database was used for testing, while Recognition performance was evaluated using recognition accuracy, sensitivity and specificity. Performance evaluation results of the developed system gave 89.44%, 49.80% and 49.77% recognition accuracy, sensitivity and specificity respectively. The system can be deployed in biometric identification systems and surveillance applications where age variations are pervasive.

    Citing this Journal Article :

    Ojo John Adedapo, Joseph Oluwaseunoladunni, "Age invariant face recognition using fuzzy local binary pattern and artificial neural network classifier", https://www.ijltet.org/journal_details.php?id=938&j_id=4727, Volume 11 Issue 4 - October 2018, 62-67, #ijltetorg