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Fourier Transform Coding-based Techniques for Lossless Iris Image Compression
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     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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Publication Date
Fri May 16 2014
Journal Name
International Journal Of Computer Applications
Lossless Image Compression based on Predictive Coding and Bit Plane Slicing
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Publication Date
Sat Jun 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Hierarchal Polynomial Coding of Grayscale Lossless Image Compression
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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Iris Data Compression Based on Hexa-Data Coding
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Iris research is focused on developing techniques for identifying and locating relevant biometric features, accurate segmentation and efficient computation while lending themselves to compression methods. Most iris segmentation methods are based on complex modelling of traits and characteristics which, in turn, reduce the effectiveness of the system being used as a real time system. This paper introduces a novel parameterized technique for iris segmentation. The method is based on a number of steps starting from converting grayscale eye image to a bit plane representation, selection of the most significant bit planes followed by a parameterization of the iris location resulting in an accurate segmentation of the iris from the origin

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Publication Date
Wed Jun 01 2022
Journal Name
V. International Scientific Congress Of Pure, Applied And Technological Sciences
Lightweight Image Compression Using Polynomial and Transform Coding
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Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Lossless Image Compression using Adaptive Predictive Coding of Selected Seed Values
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Publication Date
Fri Nov 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Adaptive Color Image Compression of Hybrid Coding and Inter Differentiation Based Techniques
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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Recursive Prediction for Lossless Image Compression
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     This paper introduced an algorithm for lossless image compression to compress natural and medical images. It is based on utilizing various casual fixed predictors of one or two dimension to get rid of the correlation or spatial redundancy embedded between image pixel values then a recursive polynomial model of a linear base is used.

The experimental results of the proposed compression method are promising in terms of preserving the details and the quality of the reconstructed images as well improving the compression ratio as compared with the extracted results of a traditional linear predicting coding system.

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Publication Date
Wed Jul 06 2022
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Image Compression using Polynomial Coding Techniques: A review
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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
Image Compression Based on Arithmetic Coding Algorithm
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The past years have seen a rapid development in the area of image compression techniques, mainly due to the need of fast and efficient techniques for storage and transmission of data among individuals. Compression is the process of representing the data in a compact form rather than in its original or incompact form. In this paper, integer implementation of Arithmetic Coding (AC) and Discreet Cosine Transform (DCT) were applied to colored images. The DCT was applied using the YCbCr color model. The transformed image was then quantized with the standard quantization tables for luminance and chrominance. The quantized coefficients were scanned by zigzag scan and the output was encoded using AC. The results showed a decent compression ratio

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Publication Date
Mon Mar 20 2023
Journal Name
2023 International Conference On Information Technology, Applied Mathematics And Statistics (icitams)
Hybrid Color Image Compression Using Signals Decomposition with Lossy and Lossless Coding Schemes
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