A novel iris recognition algorithm

Goal of the proposed iris recognition is to recognize human identity through the textural characteristics of one´s iris muscular patterns. Even though eye color is dependent on heredity, in contrast to this, iris is independent and uncorrelated even for twins. Out of various biometrics such as finger and hand geometry, face, ear and voice recognition, iris recognition has been acknowledged as one of the most accurate biometric modalities because of its high recognition rate. In this proposed iris recognition method, pupil localization is done by using negative function and four neighbours method so that irrespective of pupil´s contour, either circle or ellipse, the pupil´s boundary is detected accurately. For iris outer boundary detection, contrast enhancement, special wedges and thresholding techniques are used to isolate the specific iris regions without eyelid and eyelash occlusions. Now the resultant iris portion alone is transformed into polar coordinate system for normalization process. Histogram equalization technique is used for enhancing the normalized iris image. For feature extraction and matching process, cumulative sum-based change analysis and hamming distance are employed. When compared with the existing algorithms, this proposed algorithm is robust, accurate and also has low computational time and complexity.