Automatic recognition of the human iris is essential for the purpose of personal identification and verification from eye images. The human iris is known to possess structures that are distinct and unique to each individual. Accurate classification, however, depends on proper segmentation of the iris and the pupil. In this paper, we present a new method for automatically localizing and segmenting the iris with no operator intervention. Circular region growing is first used to localize the eye's centroid. We then utilize several geometrical features of the eye to constraint a model built in the polar image space. The model employs knowledge of anatomical attributes as well as gradient information to extract the iris boundaries. Applying this method to 352 images revealed 92% segmentation accuracy. The algorithm has shown to be effective in various levels of illumination and for images with large field of view containing other facial features.


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    Title :

    Automatic segmentation of iris images for the purpose of identification


    Contributors:
    Zaim, A. (author)


    Publication date :

    2005-01-01


    Size :

    107085 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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