Abstract
this research is considered to be a research to attract attention to the 3D iris compression to store the database of the iris. Actually, the 3D iris database cannot be found and in trying to solve this problem 2D iris database images are converted to 3D images just to implement the compression techniques used in 3D domain to test it and give an approximation results or to focus on this new direction in research. In this research a fully automated 3D iris compression and recognition system is presented. We use spherical based wavelet coefficients for efficient representation of the 3D iris. The spherical wavelet transformation is used to decompose the iris image into multi-resolution sub images. The representation of features based on spherical wavelet parameterization of the iris image was proposed for the 3D iris compression system. To evaluate the performance of the proposed approach, experiments were performed on the CASIA Iris database. Experimental results show that the spherical wavelet coefficients yield excellent compression capabilities with minimal set of features. Haar wavelet coefficients extracted from the iris image was found to generate good recognition results.
Highlights
Biometric identification is the process of associating an identity to the input biometric data by comparing it against the enrolled identities in a database [1]
Iris localization that detects the inner and outer boundaries of iris [44], [45] and iris normalization, in this step, iris image is converted from Cartesian coordinates to Polar coordinates
We are not focusing on the segmentation instead we are interested in iris compression we have used the existing algorithms [42]for image preprocessing normalization feature extraction and segmentation but focusing only on iris compression and matching algorithm
Summary
Biometric identification is the process of associating an identity to the input biometric data by comparing it against the enrolled identities in a database [1]. To design and implement robust systems capable of mass deployment, one needs to address key issues, such as human factors, environmental conditions, system interoperability, and image standard [2].The iris, the colored portion of the eye surrounding the pupil, contains unique patterns which are prominent under nearinfrared illumination These patterns remain stable from a very young age, barring trauma or disease, allowing accurate identification with a very high level of confidence. The 3D iris database cannot be found and in trying to solve this problem 2D iris database images are converted to 3D images just to implement the compression techniques used in 3D domain to test it and give an approximation results or to focus on this new direction in research.
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