Abstract
It is inevitable to capture a portion of iris images with motion blur during iris recognition. The texture details on iris patterns are lost in motion blurred images so it may cause recognition performance degradation. This paper presents a first systematic study on the issue of motion blurred iris image recognition. Firstly, the reason of generating motion blurred iris images is analyzed. Secondly, the influence of the strength and the direction of motion blur on the accuracy of iris recognition is quantitatively investigated. Thirdly, we propose two solutions which can be used separately or jointly to improve recognition accuracy on motion blurred iris images. The first solution is a deblur-ring method in preprocessing stage and the other is a motion blur weight map with two generation methods in matching stage. Experimental results on both synthetic and real-world motion blurred iris image databases demonstrate the effectiveness and efficiency of our methods.
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