CLASSIFIED VECTOR QUANTIZATION AND ITS APLICATION ON COMPRESSION OF IRIS IMAGES IN THE SAFETY OF MARINE SYSTEMS

• Published in: Promet - Traffic&Transportation Vol. 28; no. 2; p. 125
• Main Authors: Čorić, Mirko, Lušić, Zvonimir, Gudelj, Anita
• Format: Web Resource
• Language: English
• Published: Fakultet prometnih znanosti Sveučilišta u Zagrebu 25.04.2016
• Subjects: classified vector quantization; iris recognition; marine security
• ISSN: 0353-5320; 1848-4069
• DOI: 10.7307/ptt.v28i2.1707

As a standard, 512 byte IrisCode templates developed with specific algorithms are stored in databases and used in iris recognition process. Future tendencies are to use real images rather than IrisCode templates in the iris recognition process. Many of current portable iris systems use portable devices (e.g. iris scanners) which are often required to transmit image or template over communication channel. Image compression can be used in order to reduce the transmission time and storage capacities. Classified Vector Quantization (CVQ) and ordinary Vector Quantization (VQ) are used for compression of grayscale iris images collected from one of the available public databases of iris images. Results show that both compression methods are significantly more effective when applied over iris images with respect to average images from everyday environments since iris images are fairly uniform and contain low contrast levels. Originally, CVQ is used to improve the quality of edges of compressed images because they are the most important part of image for a visual impression on human. Comparison and major advantage of CVQ over ordinary VQ in terms of significant time reduction needed for iris images to be coded is presented, and therefore a new important application of CVQ is highlighted.