M²BRTPC: A Novel Modified Multimodal Biometric Recognition for Toddlers and Pre-School Children Approach

Abstract

Abstract A biometric system based on the characteristics of adults recently achieved an outstanding result. Over the last few decades, many applications have been developed for adults, such as fingerprint, face, iris, and hand-vein. Infant identification suffers from many problems and does not enroll all possible ages. Identifying children using one or any biometric features is the first step in ensuring that they are recognized before the law and that their rights are guaranteed. From another perspective, this prevents baby swaps in hospitals, Identifying Missing Children and Civil ID Programs. This paper introduces an approach for Multimodal Biometric Recognition for Toddlers and Pre-School Children. The focus is on finding a conclusion regarding how to identify a child of different ages using as few biometric features as possible, for instance, fingerprints, faces, iris, etc. The proposed approach uses a dataset containing iris and fingerprint modalities of more than 100 children (aged 18 months to 4 years) and creates a new database. There are two phases in the proposed approach: Enrollment and Testing. During the enrollment phase, there are four steps, after which the extracting features are stored in the new database. There are five stages in the testing module; after creating the template, it compares it with the created database and finds the matching child. A Fingerprint Extraction Tool is also proposed for extracting features from fingerprint images. According to the experimental results, the proposed approach enhances performance by 14.75 to 18.75%.