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Tuesday, July 29, 2008



Reliable automatic recognition of persons has long been an attractive goal. As in all pattern recognition problems, the key issue is the relation between inter-class and intra-class variability. Objects can be reliably classified only if the variability among different instances of a given class is less than the variability between different classes. For example in face recognition, difficulties arise from the fact that the face is a changeable social organ displaying a variety of expressions, as well as being an active 3D object whose image varies with viewing angle, pose, illumination, accoutrements and age. Against this intra-class (same face) variability, inter-class variability is limited because different faces possess the same basic set of features, in the same canonical geometry.
Among the physiological characteristics, iris patterns have a wonderful and abundant structure and full of complex textures. The coloured part of the eye contains delicate patterns that vary randomly from person to person, offering a powerful means of identification. These patterns are well protected from the external environment and can not be stolen, copied, stored or imitated. Although small (11 mm) and some times problematic to image, the iris has the great mathematical advantage, that its pattern variability among different persons is enormous. As a planar object, its image is relatively insensitive to angle of illumination. Iris begins to form in the third month of gestation and the structures creating its pattern are largely complete by the eighth month and remain stable throughout the life.


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