Adaptive Reflection Detection and Location in Iris Biometric Images by Using Computational Intelligence Techniques

作者：Scotti Fabio^*; Piuri Vincenzo

来源：IEEE Transactions on Instrumentation and Measurement, 2010, 59(7): 1825-1833.

DOI：10.1109/TIM.2009.2030866

• Biometric system
• iris
• neural networks
• radial symmetry transform (RST)

Iris-based biometric systems identify individuals by comparing the characteristics of the iris captured by suited sensors. When reflections are present in the iris image, the portion of the iris covered by the reflections should not be considered in the comparison since it may produce erroneous matches. This paper presents an adaptive design methodology for reflection detection and location in iris biometric images based on inductive classifiers, such as neural networks. In particular, this paper proposes a set of features that can be extracted and measured from the iris image and that can effectively be used to achieve an accurate identification of the reflection position using a trained classifier. In addition, the use of radial symmetry transform (RST) is presented to identify the reflections in iris images. The proposed design methodology is general and can be used in any biometric system based on iris images.

• 出版日期2010-7