A new class of Zernike moments for computer vision applications

Papakostas, George A.; Boutalis, Yiannis S.; Karras, D.A.; Mertzios, B.G.

doi:10.1016/j.ins.2007.01.010

Cited by 111 publications

(56 citation statements)

References 23 publications

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“…Orthogonal image moments have gained significant attention as compact content descriptors with minimum information redundancy [9], in pattern recognition [10], computer vision [11][12][13] and image processing [14] applications.…”

Section: Watermarking By the Methods Of Momentsmentioning

confidence: 99%

Fuzzy knowledge-based adaptive image watermarking by the method of moments

Papakostas

Tsougenis

Koulouriotis

2016

Complex Intell. Syst.

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A novel adaptive image watermarking methodology, robust to common signal processing attacks, is proposed in this paper. The introduced watermarking scheme uses prior knowledge in the form of IF-THEN fuzzy rules to intelligently decide the appropriate embedding strength applied to each coefficient in the moment domain carrying the watermark information. Initially, the prior knowledge regarding the amount of watermark information each moment coefficient of the original image has the capacity to hide is used to build an optimized rule-based fuzzy inference system. The resulted system is able to provide the appropriate embedding strength for each moment coefficient, ensuring high imperceptible watermarked images and high fidelity in watermark extraction. Extensive experiments under several attacking conditions demonstrate that the proposed methodology can improve the robustness of the watermarked images by a significant factor up to 32 %, without affecting their optical quality.

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Section: Watermarking By the Methods Of Momentsmentioning

confidence: 99%

Fuzzy knowledge-based adaptive image watermarking by the method of moments

Papakostas

Tsougenis

Koulouriotis

2016

Complex Intell. Syst.

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“…There are proposed several techniques to increase the accuracy and efficiency of moment descriptors. (Zhang, 2000), (Papakostas et al, 2007(Papakostas et al, , 2009. (Sookhanaphibarn & Lursinsap, 2006).…”

Section: Low and Mid-level Vision Platform Orthogonal Variant Modelsmentioning

confidence: 99%

Real-Time Motion Processing Estimation Methods in Embedded Systems

Botella¹,

González²

2012

Real-Time Systems, Architecture, Scheduling, and Application

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“…The first introduction of image moments for classification purposes was performed by Hu [4], and then developed into other families, such as Legendre [5], Zernike [6], Pseudo- problem, an improved algorithm to compute Pseudo-Jacobi-Fourier moments in the Cartesian coordinate system is proposed in this paper. This improved algorithm is applied to classify the microscopic images of helminth eggs by using Euclidean distance classifier [14], and the recognition rate is 92.2%.…”

Section: Introductionmentioning

confidence: 99%

An Improved Algorithm for Pseduo-Jacobi-Fourier Moments

Amu¹

2017

OPJ

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Image moments have been used in many research fields of the engineering. However, the related computation of invariant moments mostly adopted the polar coordinate system, which not only increase the computational load, but also cause large quantized error. To solve this problem, an improved algorithm to compute Pseudo-Jacobi-Fourier moments in the Cartesian coordinate system is proposed in this paper. The experimental results show that the reconstructed image with improved PJFM's has more advantages than polar coordinate system, such as more information, fewer moments, less time consuming. And the recognition rate of the microscopic images of 8 helminth eggs was also higher than in polar coordinate system.

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A new class of Zernike moments for computer vision applications

Cited by 111 publications

References 23 publications

Fuzzy knowledge-based adaptive image watermarking by the method of moments

Fuzzy knowledge-based adaptive image watermarking by the method of moments

Real-Time Motion Processing Estimation Methods in Embedded Systems

An Improved Algorithm for Pseduo-Jacobi-Fourier Moments

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