Recognition of human face is an important domain in unique identification of humans. It is currently being widely used in many industrial applications, such as video monitoring systems, human–computer interaction, and automatic gate control systems and for securing networks. Every university uses some method of attendance to keep a record of the number of students or people who attended that particular lecture. This paper delineates a method for taking attendance of people in a classroom which integrates the face recognition technology using local binary patterns histograms (LBPH) algorithm, along with face detection by Haar feature-based cascades and distance-based clustering. The proposed system records the attendance of the people in a classroom environment autonomously and provides the user with an output as a spreadsheet describing the attendance. © 2019, Springer Nature Singapore Pte Ltd.