• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.459-464
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• 2003

This paper proposes the use of a wavelet based image transform algorithm in human iris recognition method and the effectiveness of this technique will be determined in preprocessing of extracting Iris image from the user´s eye obtained by imaging device such as CCD Camera or due to torsional rotation of the eye, and it also resolves the problem caused by invariant under translations and dilations due to tilt of the head. This technique values through the proposed translation-invariant wavelet transform algorithm rather than the conventional wavelet transform method. Therefore we extracted the best-matching iris feature values and compared the stored feature codes with the incoming data to identify the user. As result of our experimentation, this technique demonstrate the significant advantage over verification when it compares with other general types of wavelet algorithm in the measure of FAR & FRR.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.55-62
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• 2012

EZW, also known as Embedded Zerotree Wavelet, is a technique that allows transforming original images into wavelet, then again compressing images using the transformed data. This algorithm demonstrates a simple structure and remarkable effectiveness. This paper has reformed the EZW to improve a compression efficiency. Fundamentally, EZW evaluates the priority level of wavelet-transformed data and stores them into four different categories considering the priority level of the data as well as their location information. The four categories are represented as the symbols P, N, Z, and T. Here, P and N correspond to the volume of data and the priority level whereas Z and T show the location information of data. Each letter is stored through the process of dominant pass. However, here is when the data of Z and T are stored redundantly which lead to unnecessary increase of data volume. In this paper, we propose a modified version of Embedded Zerotree Wavelet algorithm, which is designed to efficiently reduce the volume of redundantly stored data using four additionally inserted symbols. We name it EEZW, Extended Embedded Zerotree Wavelet. The proposed algorithm demonstrates the efficiency verified by a number of image and confirms an outstanding result through the PSNR(Peak Signal To Noise Rate) values, which measure their quality of images.