Noise reduction for iris recognition using adaptive fuzzy filtering

• Main Authors: Dehkordi, A. B., Abu-Bakar, S. A. R.
• Format: Conference or Workshop Item
• Published: Institute of Electrical and Electronics Engineers Inc. 2016
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/73385/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-84971596764&doi=10.1109%2fICSIPA.2015.7412223&partnerID=40&md5=a510eebeef3fd8fad0fc02bfd902ba8b

Reduction of influences of noise is an important stage in the iris recognition systems. In order to reduce effects of noise such as, eyelashes, eyelids and light illumination, this paper proposes noise reduction method based on an adaptive fuzzy filtering. The proposed method has low complexity and adaptive window size of filling filter. The Fuzzification is based on density of noise pixels within the filter's window and intensity values of noise and iris patterns. The Adaptive window size of filter enables the filling filter to perform noise reduction for different densities of noise pixels in the iris region. The results of applying proposed adaptive fuzzy filtering method on the CASIA V3.0 iris database, with genuine acceptance rate equals 99.72% show the success of the proposed method.