Image Quality Measures for Gender Classification

The major problem that we are facing in biometric systems is the use of fake biometric identifiers. Fake biometric identifiers can be of the form where one person imitates as another by falsifying data and thereby gaining an illegitimate advantage. This can be achieved either by using fake self manufactured synthetic or reconstructed samples. Gender classification has become an essential part in most human computer interactions especially in high security areas where gender restrictions are provided. In this paper, software based multi-biometric system that is used to classify real and fake face samples and a gender classification are presented. The main objective of the paper is to improve biometric detection in a fast, non intrusive way which maintains the generality that is lacking in other anti-spoofing methods. The proposed method incorporates liveness detection, extracts 25 general image quality measures from the input image and then classifies the input into real or fake sample. Algorithm for Gender classification is developed in accordance with the facial features. There features are classified into two i) appearance based ii) Geometric based. The image quality assessment algorithm is developed and tested with ATVS database. The gender classification with image quality assessment is developed and tested with medical students database. DOI: 10.17762/ijritcc2321-8169.15017