International Journal of Scientific Research and Engineering Development

An essential administrative task in educational institutions, attendance management has a direct impact on student performance monitoring and academic evaluation. Conventional manual attendance procedures are laborious, prone to human mistake, and susceptible to proxy attendance. This project offers a Web-Based Automated Attendance Management System with Facial Recognition combined with a distributed microservices architecture to get around these restrictions. The suggested method automates the process of marking attendance by using computer vision techniques for face identification and recognition. Haar Cascade classifiers are used for facial detection, while the OpenCV library's Local Binary Patterns Histogram technique is used for recognition. Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.

Dr.S.Brindha, Dr.S.Ravichandran, Sajith Balaji Sarvesh,"Face Recognition Using Deep Learning Method for Active Face Shape Model in Academic Action" International Journal of Scientific Research and Engineering Development, V9(4): Page(40-52) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.