Robust Detection of Textured Contact Lenses in Iris Recognition Using BSIF

—This paper considers three issues that arise in creating an algorithm for robust detection of textured contact lenses in iris recognition images. One issue is whether accurate segmentation of the iris region is required in order to achieve accurate detection of textured contact lenses. Our experimental results suggest that accurate iris segmentation is not required. A second issue is whether an algorithm trained on images acquired from one sensor will generalize well to images acquired from a different sensor. Our results suggest that using a novel iris sensor can significantly degrade the correct classification rate of a detection algorithm trained with images from a different sensor. A third issue is how well a detector generalizes to a brand of textured contact lenses not seen in the training data. This work shows that a novel textured lens type may have a significant impact on the performance of textured lens detection.

• Type: Journal
• Year: 2015
• Where: ACCESS
• Authors: James S. Doyle Jr., Kevin W. Bowyer
• Keywords: ACCESS 2015