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In this chapter we reviewed both the theoretical and practical aspects of iris recognition. An iris recognition system usually consists of subfunctional units: (1) iris acquisition, (2) image preprocessing, (3) iris feature extraction, and (4) pattern recognition and matching. We introduced different types of iris acquisition devices and analyzed their strengths and weaknesses. Image preprocessing is an extremely important step for all computer vision and pattern recognition problems because higher-quality images will always produce better results. For iris recognition systems, the speci c characteristics of the annular shape of the iris region call for a coordinate transformation that can compensate for rotational and non-af ne variations in images. Furthermore, contrast enhancement methods can improve the quality of the images by raising the contrast level locally. The goal of feature extraction is to extract discriminant information in raw iris patterns. In this chapter we analyzed different feature extraction schemes proposed by different researchers. Wavelet analysis has been widely used due to its power in space-frequency domain analysis. Image pyramids are also used to inspect detailed information in iris patterns under different scales of image size. The recognition algorithm strongly depends on the feature extraction scheme. Good recognition algorithms are expected to give (a) high distance scores for irises that come from different eyes and (b) low distance scores for irises that come from the
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same eye. Another important issue we considered is how fast the matching process can be achieved. Finally, we reviewed a recent work that takes into account the local deformations of the iris patterns, which we model with probabilistic graphical models. The reported experimental results show the superiority of local patch matching versus global pattern matching. At the end, we also introduced one example of large-scale deployment of iris recognition system, happening in the UAE. The system can perform iris matching with 420,000 iris templates in the database in less than 1 s, and the system is scalable to allow more templates to be enrolled. The UAE iris recognition system proves that iris recognition is feasible, practical, and accurate. This example showed iris recognition has emerged as the most promising biometric technology and has been used successfully in enhancing national security and protecting a country.
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