Gaze of the human eye may act as a communication medium for limb disabled people to interact with computers. In order to determine gaze direction, the first necessary step in image processing is segmentation of iris from entire eye image. In this paper Daugman's algorithm is implemented that uses Integro Differential Operator (IDO) to differentiate iris boundary from sclera part of eye and to find the centroid, to determine where the person is looking. Also the computation time required for IDO to scan the image is minimized by applying the operator only to the local minima pixels in the image. The algorithm is implemented in MATLAB and tested on static eye images selected from the CASIA database as well as on the eye images captured by an iPhone 4s, 8 MP camera with a resolution of 3264×2448 pixels. This method can be useful in eye tracking to handle the input devices of computer like keyboard and mouse.

Human Computer Interaction is a trend-in technology. Working in this field, we have developed a system to provide a solution to the limb disabled people to interact with computer. Different algorithms are implemented in this paper, to estimate the gaze of user to recognize the reference key. The first step performed on each input frame is the face detection, which is achieved using Viola-Jones algorithm, whereas Circular Hough Transform is used to locate the pupil in eye image. Similarly glint (a small and intense dot inside the pupil image) is detected by the blob analysis method. Using these pupil location and glint location, gaze direction of the user is estimated. With these functions, the user is able to handle input devices of a computer like keyboard and helps to recognize the key to be pressed. Further the type-in process is continued with the blinking phenomenon which is detected using template matching method. Currently the system is limited to 4-key keypad. The system is also designed with opening some window application softwares like Skype, media player etc. which are useful to the limb disable people. The camera used in this application, to access video is Logitech HD 720p webcam (C310) and the software implementation part is done in MATLAB. The system is tested under various environmental conditions, giving the appreciable results and speed.