With the enlargement of mankind's activity range, the significance for person's status identity is becoming more and
more important. So many different techniques for person's status identity were proposed for this practical usage.
Conventional person's status identity methods like password and identification card are not always reliable. A wide
variety of biometrics has been developed for this challenge. Among those biologic characteristics, iris pattern gains
increasing attention for its stability, reliability, uniqueness, noninvasiveness and difficult to counterfeit. The distinct
merits of the iris lead to its high reliability for personal identification. So the iris identification technique had become hot
research point in the past several years.
This paper presents an efficient algorithm for iris recognition using gray-level co-occurrence matrix(GLCM) and Discrete
Cosine transform(DCT). To obtain more representative iris features, features from space and DCT transformation domain
are extracted. Both GLCM and DCT are applied on the iris image to form the feature sequence in this paper. The
combination of GLCM and DCT makes the iris feature more distinct. Upon GLCM and DCT the eigenvector of iris
extracted, which reflects features of spatial transformation and frequency transformation. Experimental results show that
the algorithm is effective and feasible with iris recognition.