Efficient iris Recognition System to Improve Performance Measure for live videos

Iris recognition is regarded as the most reliable and accurate biometric identification system available. Iris substantiation is one of the most successful applications in video analysis and image processing. In this project, several proficient approaches are proposed to increasing the performance measures of Iris Recognition system for Live Videos. Face detection is the first and foremost step, efficient face detection algorithm such as Viola algorithm is used for this purpose. Using feature extraction process left and right eye are isolated and stored in the database. Next is the Iris Segmentation process. Iris segm recognition. The main purposes are to improve accuracy and to reduce computational time of iris localization. Briefly, this approach tries to explore regions of interests (ROI) among image regions and to or more remaining regions. A new eyelash detection algorithm based on direction filter to achieve a low rate of eyelash misclassification is proposed. Final step is the Iris Recognition, in order to speed up the response time and to enhance the code searching speed Euclidean Distance Classifier is used to efficiently recognize the iris images from the database.