Using Artificial Neural Networks and Feature Saliency Techniques for Improved Iris Segmentation

—One of the basic challenges to robust iris recognition is iris segmentation. This paper proposes the use of a feature saliency algorithm and an artificial neural network to perform iris segmentation. Many current Iris segmentation approaches assume a circular shape for the iris boundary if the iris is directly facing the camera. Occlusion by the eyelid can cause the visible boundary to have an irregular shape. In our approach an artificial neural network is used to statistically classify each pixel of an iris image with no assumption of circularity. First, a feed-forward feature saliency technique is performed to determine which combination of features contains the greatest discriminatory information. Image brightness, local moments, local orientated energy measurements and relative pixel location are evaluated for saliency. Next, the set of salient features is used as the input to a multi-layer perceptron feed-forward artificial neural network trained for classification. Testing sh...

• Type: Conference
• Year: 2007
• Where: IJCNN
• Authors: Randy P. Broussard, Lauren R. Kennell, David L. Soldan, Robert W. Ives
• Keywords: Artificial Neural Network, IJCNN 2007, Iris Boundary, Iris Segmentation