Design and Realization of Circular Contourlet Transform

Abdul–Jabbar, Jassim M.; Fathee, Hala N.

doi:10.33899/rengj.2010.31518

Cited by 3 publications

(4 citation statements)

References 12 publications

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“…The designed 2D filters using circular-support schemes can function as a 2D wavelet filter bank. One of the main benefits of circular-support schemes is that they can possess better performance than rectangular-support schemes when it is desired to extract as much low-frequency information as possible in a 2D low-pass filtering channel (or as much high-frequency information as possible in a 2D high-pass filtering channel) [25]. It was shown in [24] that the 2D circular-support decomposition scheme can effectively improve the operation of extracting both approximation and detail coefficients from original images using 2D circular filters instead of using the traditional two-stage 1D filter decomposition in the classical 2D discrete wavelet transform.…”

Section: The Proposed Iris Recognition Methodsmentioning

confidence: 99%

Efficient Unconstrained Iris Recognition System Based on CCT‐Like Mask Filter Bank

Fathee

Uçan

Abdul–Jabbar

et al. 2019

Mathematical Problems in Engineering

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In this paper, a new personal identification method based on unconstrained iris recognition is presented. We apply a nontraditional step for feature extraction where a new circular contourlet filter bank is used to capture the iris characteristics. This idea is based on a new geometrical image transform called the circular contourlet transform (CCT). An efficient multilevel and multidirectional contourlet decomposition method is needed to form a reduced-length quantized feature vector with improved performance. The CCT transform provides both multiscale and multioriented analysis of iris features. Circular contourlet-like mask filters can be used with shapes just like the 2D circular-support regions in different scales and directions. A reduced recognition system is realized using a single branch of the whole decomposition bank, highlighting a system realization with lower complexity and fewer computations. In the proposed recognition system, only five out of seven elements of the gray level cooccurrence matrix are required in the creation of the feature vector, which leads to a further reduction in computations. In addition, the highly discriminative frequency regions due to the use of circular-support decompositions can result in highly accurate feature vectors, reflecting good recognition rates for the proposed system. It is shown that the proposed system has encouraging performance in terms of high recognition rates and a reduced number of elements of the feature vector. This reflects reliable and rapid recognition properties. In addition, some promising characteristics of the system are apparent since it can efficiently be realized with lower computation complexity.

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Section: The Proposed Iris Recognition Methodsmentioning

confidence: 99%

Efficient Unconstrained Iris Recognition System Based on CCT‐Like Mask Filter Bank

Fathee

Uçan

Abdul–Jabbar

et al. 2019

Mathematical Problems in Engineering

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“…Haar 2-tap wavelet is chosen as a reference filter for the architecture of 2-D filter bank. The coefficients of the low-pass h 0 and the high-pass h 1 decomposition filters corresponding to this wavelet type are shown in Table 1 [7]. Table 1-Haar 2-tap wavelet coefficients.…”

Section: Haar Wavelet Transformmentioning

confidence: 99%

“…A 2-D circular-support wavelet transform (2-D CSWT) is proposed in this paper as a new geometrical image transform, which can efficiently represent images using circular split 2-D spectral schemes ( circularly -decomposed frequency subspaces ). Such schemes are known to give better performance than rectangular-support schemes when it is desired to extract as low frequency information as possible in a 2-D low-pass filtering channel and as high frequency information as possible in a 2-D highpass filtering channel [7]. The corresponding 2-D wavelet filters are designed.…”

Section: Introductionmentioning

confidence: 99%

A Multiplier-less Implementation of Two-Dimensional Circular-Support Wavelet Transform on FPGA

Dawood¹,

Abede²,

Abdul–Jabbar³

2013

IJEEE

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In this paper, a two-dimensional (2-D) circular-support wavelet transform (2-D CSWT) is presented. 2-D CSWT is a new geometrical image transform, which can efficiently represent images using 2-D circular spectral split schemes (circularlydecomposed frequency subspaces). 2-D all-pass functions and lattice structure are used to produce 1-level circular symmetric 2-D discrete wavelet transform with approximate linear phase 2-D filters. The classical one-dimensional (1-D) analysis Haar filter bank branches H 0 (z) and H 1 (z) which work as low-pass and high-pass filters, respectively are transformed into their 2-D counterparts H 0 (z 1 ,z 2) and H 1 (z 1 ,z 2) by applying a circular-support version of the digital spectral transformation (DST). The designed 2-D wavelet filter bank is realized in a separable architecture. The proposed architecture is simulated using Matlab program to measure the deflection ratio (DR) of the high frequency coefficient to evaluate its performance and compare it with the performance of the classical 2-D wavelet architecture. The correlation factor between the input and reconstructed images is also calculated for both architectures. The FPGA (Spartan-3E) Kit is used to implement the resulting architecture in a multiplier-less manner and to calculate the die area and the critical path or maximum frequency of operation. The achieved multiplier-less implementation takes a very small area from FPGA Kit (the die area in 3-level wavelet decomposition takes 300 slices with 7% occupation ratio only at a maximum frequency of 198.447 MHz).

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“…, which correspond to the subbands indexed as in Figure (10). From the multiscale analysis of the previous LP stage, the DFB in the contourlet filter bank utilizes orthogonal filters and when such DFB is applied to the difference image (detail) subspaces, the resulting detail directional subspaces…”

Section: -Multidirectionalmentioning

confidence: 99%

Hybrid System for Speech Coding Based on Contourlet Transformation

Alsaif¹,

Albadrani²

2013

AL-Rafidain Journal of Computer Sciences and Mathematics

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The main objective of speech coding is to allow the transmission of speech over digital channel of the highest speech quality and least possible bit rate, beside the security purpose.In this paper, the speech was coded by transforming it applying (which is often single dimension) into a two dimensional array to be suitable for transferring the countourlet transformation. Applied EZC (Embedded Zero tree Contourlet) algorithm, then is applied to the Huffman coding on the results of EZC, and used RLE (Run Length Encoding).The above idea gave the ability for coding, compression with retrieved information of high accuracy, using some measurements for quality measured of reconstructed signal, and found results show high similarity between the original and reconstructed signal.

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Design and Realization of Circular Contourlet Transform

Cited by 3 publications

References 12 publications

Efficient Unconstrained Iris Recognition System Based on CCT‐Like Mask Filter Bank

Efficient Unconstrained Iris Recognition System Based on CCT‐Like Mask Filter Bank

A Multiplier-less Implementation of Two-Dimensional Circular-Support Wavelet Transform on FPGA

Hybrid System for Speech Coding Based on Contourlet Transformation

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