Attendance monitoring is very important at schools, colleges, offices and many more places. Conventional attendance system takes more time to record attendance and sometimes there is a chance of proxy attendance. Even in biometric attendance system also students need to give thumb impression, which consumes time. To overcome the problems of conventional and biometric attendance systems smart attendance systems came in to picture. This paper proposes a smart contactless attendance recording system for classroom students using face recognition technique. Initially students need to register with name, roll number and set of images and this information will be saved as database. Next an image of each student is captured and image processing is done to extract facial traits, and then compares those features to a database of people who have registered with the system. The attendance is automatically marked in excel sheet if a match is discovered. Face detection and recognition are done with the help of Haar cascade classifier, the Local Binary Pattern Histogram methods and K nearest neighbour algorithms. From simulations it is observed that K nearest neighbours algorithm is more accurate but requires more space and time compared to Haar cascade classifier.