Eye Detection Model for Assessing the Working Capacities of Employees

Abstract

The model introduced in the paper deals with the assessment of the working capacity of employees by iris recognition, and pupil recognition. Employers gravitate to ensure that workers who come to work have maximum efficiency at work. Eye detection model for assessing the working capacities of employees has that goal. The CNN (Convolutional Neural Networks) recognize the eye on the employee’s face and selects the best image for further processing. The image selected by CNN is further processed using the Hough transformation. The post-process involves the application of Canny edge detection and segmentation to find a circle representing the iris. Using the iris recognition algorithm, we determine deviant states and assess the working ability of the employee. The model was tested on a predetermined dataset and the test results are about 90% accurate.