A novel hybrid biometric software application for facial recognition considering uncontrollable environmental conditions

• Published in: Healthcare analytics (New York, N.Y.) Vol. 3; p. 100156
• Main Authors: H.R., Vijaya Kumar, M., Mathivanan
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.11.2023; Elsevier
• Subjects: Biometric applications; Classification; Face recognition; Health Systems Science; Logarithmic gabor; Public Health; Wavelet transform; Biometric applications; Wavelet transform; Face recognition; Logarithmic gabor; Classification
• ISSN: 2772-4425; 2772-4425
• DOI: 10.1016/j.health.2023.100156

Human face recognition research in biometric applications is a popular research subject because of its various applications and challenges, including camera type, pose, light or illumination, resolutions, wearing or not wearing glasses, and expressions, among others. This study presents a novel hybrid biometric software application for facial recognition considering uncontrollable environmental conditions. The proposed system uses two features namely, Laplace of Gaussian filter-based Discrete Wavelet Transform (LGDWT) and Discrete Cosine Transform Compressed based Log Gabor Filter (DCTLGF). The combined LGDWT and DCTLGF features were used by a Multiclass Support Vector Machine (MSVM) classifier to create the desired class label of individual faces. Our work was tested on a face dataset comprising 25 people of 200 face images which are taken using a five-megapixel low-goal web camera and yielded good results in different bounds in contrast to existing techniques. •This study presents a novel hybrid biometric software application for facial recognition.•The facial features are used by a multiclass support vector machine classifier to create the desired class.•Testing was conducted on a facial database comprising 25 people, each with 200 pictures.•A five-megapixel low-goal web camera yields good results on various boundaries contrasted with existing. techniques.