Explicit Separable two dimensional Moment Invariants for object recognition

Benouini, Rachid; Batioua, Imad; Elouariachi, Ilham; Zenkouar, Khalid; Zarghili, Arsalane

doi:10.1016/j.procs.2019.01.049

Cited by 6 publications

(2 citation statements)

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“…Discrete moments present multiple advantages as they assure a strong image representation capacity with minimal computing complexity. Moreover, they VOLUME 11, 2023 completely reconstruct the described image with minimum errors and great robustness against noise [65]. In particular, image moments are a useful technique in watermarking applications, due to the minimal reconstruction error of the watermarked image after embedding the data at the moment domain, and the good watermark extraction quality in the presence of attacks [19].…”

Section: Theoretical Background -Discrete Image Momentsmentioning

confidence: 99%

New Blind Image Moments Watermarking Method Based on Evolutionary Optimization of Embedding Parameters

Chekira,

Marzouq,

Batioua

et al. 2023

IEEE Access

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In image watermarking, the locations where the watermark is embedded in the frequency domain and the embedding strength influence the overall performance of the blind watermarking procedure. The present paper aims to propose a new blind watermarking method based on the dither modulation by developing an automatic selection of the optimum embedding parameters that guarantee high-quality watermarked images and low bit error rates during the extraction process. The proposed automatic search method for the best discrete moments subsets is based on an evolutionary algorithm and adopts a specific coding strategy with a group of genes representing the embedding positions. The second part of the chromosome is reserved for the embedding strength coding, followed by the application of different evolutionary operators on the evolution pool. Our study explores the impact of maximum generation, population size, and cutting-point positions with different crossover and mutation rates. The performances under different attack conditions are evaluated, and a comparative study is established with other conventional selection methods and other discrete transforms. Results show that our proposed optimization algorithm baptized EWIMps achieves the best trade-off between robustness and imperceptibility with a peak signal-to-noise ratio varying from 28.33 dB to 59.87 dB and a normalized cross-correlation value from 0.707 to 1.INDEX TERMS Data hiding, blind image watermarking, orthogonal discrete moments, discrete transforms, dither modulation, evolutionary algorithm.

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Section: Theoretical Background -Discrete Image Momentsmentioning

confidence: 99%

New Blind Image Moments Watermarking Method Based on Evolutionary Optimization of Embedding Parameters

Chekira,

Marzouq,

Batioua

et al. 2023

IEEE Access

Self Cite

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“…The curvelet transform represents one of the multiscale geometric transform family, which was developed to get rid of traditional multiscale representations methods such as wavelets [14,15]. The curvelet transform solved the problem of isotropic scaling of wavelet, which makes it fit for face features extraction.…”

Section: Curvelet Transformmentioning

confidence: 99%

Face recognition based on curvelets, invariant moments features and SVM

Ghazal

Abdullah

2020

TELKOMNIKA

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Recent studies highlighted on face recognition methods. In this paper, a new algorithm is proposed for face recognition by combining Fast Discrete Curvelet Transform (FDCvT) and Invariant Moments with Support vector machine (SVM), which improves rate of face recognition in various situations. The reason of using this approach depends on two things. first, Curvelet transform which is a multi-resolution method, that can efficiently represent image edge discontinuities; Second, the Invariant Moments analysis which is a statistical method that meets with the translation, rotation and scale invariance in the image. Furthermore, SVM is employed to classify the face image based on the extracted features. This process is applied on each of ORL and Yale databases to evaluate the performance of the suggested method. Experimentally, the proposed method results show that our system can compose efficient and reasonable face recognition feature, and obtain useful recognition accuracy, which is able to face and side-face states detection of persons to decrease fault rate of production.

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