A Novel Method for Coarse Iris Classification
This paper proposes a novel method for the automatic coarse classification of iris images using a box-counting method to estimate the fractal dimensions of the iris. First, the iris image is segmented into sixteen blocks, eight belonging to an upper group and eight to a lower group. We then calculate the fractal dimension value of these image blocks and take the mean value of the fractal dimension as the upper and the lower group fractal dimensions. Finally all the iris images are classified into four categories in accordance with the upper and the lower group fractal dimensions. This classification method has been tested and evaluated on 872 iris cases and the accuracy is 94.61%. When we allow for the border effect, the double threshold algorithm is 98.28% accurate.
KeywordsFractal Dimension Search Time Iris Image Image Block Border Effect
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