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Fourier Transform Coding-based Techniques for Lossless Iris Image Compression
Author(s) -
Ghadah Al-Khafaji,
Noor Rasidah Ali
Publication year - 2019
Publication title -
iraqi journal of science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.152
H-Index - 4
eISSN - 2312-1637
pISSN - 0067-2904
DOI - 10.24996/ijs.2019.60.11.23
Subject(s) - lossless compression , computer science , image compression , artificial intelligence , computer vision , lossy compression , data compression , wavelet transform , arithmetic coding , pattern recognition (psychology) , context adaptive binary arithmetic coding , image processing , wavelet , image (mathematics)
     Today, the use of iris recognition is expanding globally as the most accurate and reliable biometric feature in terms of uniqueness and robustness. The motivation for the reduction or compression of the large databases of iris images becomes an urgent requirement. In general, image compression is the process to remove the insignificant or redundant information from the image details, that implicitly makes efficient use of redundancy embedded within the image itself. In addition, it may exploit human vision or perception limitations to reduce the imperceptible information.      This paper deals with reducing the size of image, namely reducing the number of bits required in representing the image. This was performed by exploiting the transforms-based coding techniques of lossless base compression system. In these techniques, the first part looked at the traditional Fourier transform coding technique while the second part aimed at enhancing the performance of the traditional transformation techniques. This was achieved once by overcoming the inherited problems of this technique that suffers from the complex nature base, then latter by incorporating the double base coding techniques of hierarchal scheme, as  mixing of both discrete wavelet transform and zipper coding techniques.      The test results indicated that the proposed scheme produced high compression ratio with identically preserving the quality of the compressed (decoded) image.

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