Quaternion polar complex exponential transform for invariant color image description

Wang, Xiangyang; Li, Weiyi; Yang, Heng; Wang, Pei; Li, Yongwei

doi:10.1016/j.amc.2015.01.075

Cited by 43 publications

(7 citation statements)

References 26 publications

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“…This information may sometimes be an average intensity value, texture information, variance, and edge information in a different orientation. Also, many previous studies ( Karanwal & Diwaker, 2021 ; Guo et al, 2017 ; Wang et al, 2015 ; Suk & Flusser, 2009 ; Ojala, Pietikäinen & Harwood, 1996 ; Karami, Prasad & Shehata, 2017 ; Ahonen, Hadid & Pietikäinen, 2004 ; Hadid, 2008 ; Huijsmans & Sebe, 2003 ; Grangier & Bengio, 2008 ; Ali, Georgsson & Hellstrom, 2008 ; Nanni & Lumini, 2008 ; Mäenpää, Viertola & Pietikäinen, 2003 ; Turtinen, 2006 ; Heikkila & Pietikainen, 2006 ; Kellokumpu, Zhao & Pietikäinen, 2008 ; Oliver et al, 2007 ; Kluckner et al, 2007 ; Fisher, Stein & Fisher, 2005 ; Sharma, Jain & Khushboo, 2019 ) proved the high efficiency of the LBP as a local feature descriptor for the images. From the above results, we can observe that our proposed face recognition system has high accuracy and less recognition time, where the size of the extracted feature vector is relatively small compared with the other recently published methods ( Sajjad et al, 2020 ; Karami, Prasad & Shehata, 2017 ).…”

Section: Discussionmentioning

confidence: 90%

Fast and accurate face recognition system using MORSCMs-LBP on embedded circuits

Hosny

Hamad

Elkomy

et al. 2022

PeerJ Computer Science

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Because of the current COVID-19 circumstances in the world and the tremendous technological developments, it has become necessary to use this technology to combat the spread of the new coronavirus. The systems that depend on using hands, such as fingerprint systems and PINs in ATM systems, could lead to infection, so they have become undesirable and we can replace them by using facial recognition instead. With the development of technology and the availability of nano devices like the Raspberry Pi, such applications can be implemented easily. This study presents an efficient face recognition system in which the face image is taken by a standalone camera and then passed to the Raspberry Pi to extract the face features and then compare them with the database. This approach is named MORSCMs-LBP by combining two algorithms for feature extraction: Local Binary Pattern (LBP) as a local feature descriptor and radial substituted Chebyshev moments (MORSCMs) as a global feature descriptor. The significant advantage of this method is that it combines the local and global features into a single feature vector from the detected faces. The proposed approach MORSCMs-LBP has been implemented on the Raspberry Pi 4 computer model B with 1 GB of RAM using C++ OpenCV. We assessed our method on various benchmark datasets: face95 with an accuracy of 99.0278%, face96 with an accuracy of 99.4375%, and grimace with 100% accuracy. We evaluated the proposed MORSCMs-LBP technique against other recently published approaches; the comparison shows a significant improvement in favour of the proposed approach.

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Section: Discussionmentioning

confidence: 90%

Fast and accurate face recognition system using MORSCMs-LBP on embedded circuits

Hosny

Hamad

Elkomy

et al. 2022

PeerJ Computer Science

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“…Wang et al [22] showed that circular orthogonal moments are invariant to scaling when these moments are computed over the same unit disk. In the case of FrMRHFMs, these moments are circular orthogonal moments which are defined in polar coordinates over a unit disk, and computed using the circular image pixels as displayed in Fig.…”

Section: ) Invariance To Scalingmentioning

confidence: 99%

“…The successful utilization of Gaussian numerical integration method [27] in ref. [28], [29] encouraged us to utilize the same method to compute the radial kernel Utilizing (22) into (17) yields:…”

Section: Computational Frameworkmentioning

confidence: 99%

Novel Multi-Channel Fractional-Order Radial Harmonic Fourier Moments for Color Image Analysis

2020

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The classical radial harmonic Fourier moments (RHFMs) and the quaternion radial harmonic Fourier moments (QRHFMs) are gray-scale and color image descriptors. The radial harmonic functions with integer orders are not able to extract fine features from the input images. In this paper, the authors derived novel fractional-order radial harmonic functions in polar coordinates. The obtained functions are used to defined novel multi-channel fractional-order radial harmonic moments (FrMRHFMs) for color image description and analysis. The invariants to geometric transformations for these new moments are derived. A theoretical comparison between FrMRHFMs and QRHFMs is performed from the aspects of kernel function and the spectrum analysis. Numerical simulation is carried out to test these new moments in terms of image reconstruction capabilities, invariance to the similarity transformations, color image recognition and the CPU computational times. The obtained theoretical and numerical results clearly show that the proposed FrMRHFMs is superior to the QRHFMs and the existing fractional-order orthogonal moments. INDEX TERMS Color image analysis, fractional-order orthogonal moments, radial harmonic Fourier moments, rotation invariance.

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“…Consequently, the highly precise calculation of PCET moments produces highly accurate QPCR moments. Similar to [9,29], Equations 2 and 3 can be written as the lower and upper limits of the definite integrals to deal with colour images as follows:…”

Section: Feature Extractionmentioning

confidence: 99%

“…A robust CMFD scheme is proposed on the basis of quaternion polar complex exponential transform (QPCET) [9] to authenticate image originality. This study contributes to literature by selecting QPCET and making it a local feature in block-based technique.…”

Section: Introductionmentioning

confidence: 99%

Detection Copy-Move Forgery in Image Via Quaternion Polar Harmonic Transforms

2019

KSII TIIS

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Copy-move forgery (CMF) in digital images is a detrimental tampering of artefacts that requires precise detection and analysis. CMF is performed by copying and pasting a part of an image into other portions of it. Despite several efforts to detect CMF, accurate identification of noise, blur and rotated region-mediated forged image areas is still difficult. A novel algorithm is developed on the basis of quaternion polar complex exponential transform (QPCET) to detect CMF and is conducted involving a few steps. Firstly, the suspicious image is divided into overlapping blocks. Secondly, invariant features for each block are extracted using QPCET. Thirdly, the duplicated image blocks are determined using k-dimensional tree (kd-tree) block matching. Lastly, a new technique is introduced to reduce the flat region-mediated false matches. Experiments are performed on numerous images selected from the CoMoFoD database. MATLAB 2017b is used to employ the proposed method. Metrics such as correct and false detection ratios are utilised to evaluate the performance of the proposed CMF detection method. Experimental results demonstrate the precise and efficient CMF detection capacity of the proposed approach even under image distortion including rotation, scaling, additive noise, blurring, brightness, colour reduction and JPEG compression. Furthermore, our method can solve the false match problem and outperform existing ones in terms of precision and false positive rate. The proposed approach may serve as a basis for accurate digital image forensic investigations.

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Quaternion polar complex exponential transform for invariant color image description

Cited by 43 publications

References 26 publications

Fast and accurate face recognition system using MORSCMs-LBP on embedded circuits

Fast and accurate face recognition system using MORSCMs-LBP on embedded circuits

Novel Multi-Channel Fractional-Order Radial Harmonic Fourier Moments for Color Image Analysis

Detection Copy-Move Forgery in Image Via Quaternion Polar Harmonic Transforms

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