LAMP Seminar
Language and Media Processing Laboratory
Conference Room 4406
A.V. Williams Building
University of Maryland

Friday, March 20, 11 AM
Frank McFadden
National Institute of Standards Technology
Gaithersburg, MD

Personal Identification from Mugshot Ear Images


Personal identification techniques based on images have received considerable attention recently, but little attention has been paid to information in the image of the ear. This work demonstrates the effectiveness of detailed analysis of ear images, using the NIST database of real mugshots. Two innovative methods are aplied to boundary analysis. First, edge analysis is performed only along rays emanating from a point near the center of the ear, with time and quality advantages over traditional methods. Second, the innovative concept of "interpretation breeding" is introduced: two contrasting methods for finding the ear boundary are combined. Ear images are then cut out and standardized in several ways to compensate for image variations. For identification, a neural network is used to compute a distance criterion derived from several criteria, including components of an "eigenear" basis similar to Pentland's eigenfaces, one based on comparison of the most robust portion of the boundary curve, and another using an eigenbasis of relevant subregions. The best match to a random query is found 58% of the time, and the correct match is among the top 5 77% of the time. These results compare favorably with those for frontal images from the NIST mugshot database

home | language group | media group | sponsors & partners | publications | seminars | contact us | staff only
© Copyright 2001, Language and Media Processing Laboratory, University of Maryland, All rights reserved.