Method of recognizing human iris using daubechies wavelet transform

Abstract

The present invention relates to a method of recognizing the human iris using the Daubechies wavelet transform. The dimensions of characteristic vectors are initially reduced by extracting iris features from the inputted iris image signals through the Daubechies wavelet transform. Then, the binary characteristic vectors are generated by applying quantization functions to the extracted characteristic values so that the utility of human iris recognition can be improved as the storage capacity and processing time thereof can be reduced by generating low capacity characteristic vectors. By measuring the similarity between the generated characteristic vectors and the previously registered characteristic vectors, characteristic vectors indicative of the iris patterns can be realized.

Description

CLAIM OF PRIORITY[0001] This application makes reference to, incorporates the same herein, and claims all benefits accruing under 35 U.S.C. Section 119 from an application for "Method of Recognizing Human Iris Using Daubechies Wavelet Transform," filed earlier in the Korean Industrial Property Office on Mar. 6, 2001, and there duly assigned Serial No. 2001-11440.[0002] 1. Field of Invention[0003] The present invention relates to a method of recognizing the human iris and, more particularly, to a method of recognizing the human iris using the Daubechies wavelet transform to reduce the dimensions of characteristic vectors to improve the processing time.[0004] 2. Description of the Related Art[0005] An iris recognition system is used for performing the identification of an individual based on the information obtained from the analysis of the iris patterns, which are different for each individual. The iris recognition system has superior identification accuracy and thus provides excelle...

AI Technical Summary

Benefits of technology

0011] The present invention is directed to a method of forming low capacity characteristic vectors, so that the false acceptance rate (FAR) and the false rejection rate (FRR) can be re...

Problems solved by technology

However, the Harr wavelet transform has disadvantages in that the characteristic values change irregularly and rapidly.

In addition, a high resolution of the images cannot be obtained if the images are decompressed again after they have been compressed.

However, as the Daubechies wavelet functions are generally more complicated than the Harr wavelet functions, there is a disadvantage in that a larger arithmetic quantity may be needed.

Thus, there is a problem in that practicability and efficiency are undermined when the Gabor transform is used in the field if low capacity information is required.

The Ha...

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