Ives, Robert W.Bishop, Daniel A.Du, YingziBelcher, Craig2020-05-212020-05-212010-04-26Ives, R.W., Bishop, D.A., Du, Y. et al. Iris Recognition: The Consequences of Image Compression. EURASIP J. Adv. Signal Process. 2010, 680845 (2010). https://doi.org/10.1155/2010/680845https://hdl.handle.net/1805/22851Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA) is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.en-USAttribution 4.0 InternationalCompression RatioRecognition AccuracyImage CompressionIris ImageProbability Mass FunctionArticle