Tchebichef image watermarking along the edge using YCoCg-R color space for copyright protection

Ernawan, Ferda

doi:10.11591/ijece.v9i3.pp1850-1860

Cited by 21 publications

(19 citation statements)

References 17 publications

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“…energy compactness, separability, orthogonality, and even symmetry [27]. But DTT has advantages in low complexity, reduce memory and faster computation than DCT [16,28,29]. The many similarities between DCT and DTT make DTT can be used as an alternative to DCT in its use in digital image processing.…”

Section: Discrete Tchebichef Transform (Dtt)mentioning

confidence: 99%

“…In various researches on image compression [27,30,31] and image watermarking [16,18], it has been proven that DTT has a similar performance even slightly better compared to DCT. In some image watermarking researches such as [29,32] it has also been proven that DTT has a very good performance. As with DCT, DTT operations are often performed by dividing the image into small blocks, which are generally 8×8 [16,17,27,30], 4×4 [31] or 2×2 [33].…”

Section: Discrete Tchebichef Transform (Dtt)mentioning

confidence: 99%

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An Image Watermarking Method Using Discrete Tchebichef Transform and Singular Value Decomposition Based on Chaos Embedding

Setyono¹,

Setiadi²

2020

IJIES

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A good watermarking method should be robust against attacks but have good visual quality. This research proposes a combination of two transformations i.e. Tchebichef and singular value decomposition (SVD). Arnold's algorithm is also integrated to improve the security of the watermark and visual quality of the watermarked image. Arnold's transformation was carried out on the cover image with the aim to spread watermark. Furthermore, the cover image is divided into small blocks and transformed using Tchebichef. The lowest coefficient of each Tchebichef block is collected in a matrix for decomposition with SVD, then the watermark is embedded in the singular matrix. Based on the results of testing the proposed method can have excellent visual quality with PSNR values ranging from 45dB and SSIM averaging 0.998. The proposed method is also robust to various attacks such as filtering, noise addition, geometry, and signal processing.

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Section: Discrete Tchebichef Transform (Dtt)mentioning

confidence: 99%

Section: Discrete Tchebichef Transform (Dtt)mentioning

confidence: 99%

An Image Watermarking Method Using Discrete Tchebichef Transform and Singular Value Decomposition Based on Chaos Embedding

Setyono¹,

Setiadi²

2020

IJIES

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“…The Arnold transform is used to scramble the watermark image before embedding watermark in the host image. The Arnold transform is given by [23]: x y    is the transformed coordinates of image pixels. N us the number of iterations of scrambled image pixels.…”

Section: Arnold Transformmentioning

confidence: 99%

Multiple watermarking technique using optimal threshold

Alias

Ernawan

2020

IJEECS

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<span>The multiple watermarking technique has drawn more attention due to high demand for embedding more than one copyright. This paper proposes a multiple watermarking scheme using DWT-SVD by utilizing HVS characteristics. Our scheme embeds multiple watermarks in red and blue colors. The proposed scheme examines the coefficients of U orthogonal matrix for embedding and extracting watermarks. Watermarks are scrambled by Arnold transform before embedded in the host image in order provide additional security. The optimal thresholds for red and blue colors are revealed by finding a trade-off between normalized-cross correlation and imperceptibility from quantization steps. The experimental results demonstrate that our scheme achieves high resistant under JPEG and JPEG2000 compression for both inserted watermarks. </span>

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“…Although chromatic-based feature had some improvement in detection rate, the results may still not satisfactory due to minimal feature derived from the skin color. Several researchers utilized color-based such YCoCg-R in watermarking technique [15], HSV in shadow detection [16], cloth retrieval [17] and license plate detection [18].…”

Section: Introductionmentioning

confidence: 99%

A multi-color based features from facial images for automatic ethnicity identification model

Osman

Maarof

Rohani

et al. 2020

IJEECS

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<span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Ethnicity identification for demographic information has been studied for soft biometric analysis, and it is essential for human identification and verification. Ethnicity identification remains popular and receives attention in a recent year especially in automatic demographic information. Unfortunately, ethnicity identification technique using color-based feature mostly failed to determine the ethnicity classes accurately due to low properties of features in color-based. Thus, this paper purposely analyses the accuracy of the color-based ethnicity identification model from various color spaces. The proposed model involved several phases such as skin color feature extraction, feature selection, and classification. In the feature extraction process, a dynamic skin color detection is adapted to extract the skin color information from the face candidate. The multi-color feature was formed from the descriptive statistical model. Feature selection technique applied to reduce the feature space dimensionality. Finally, the proposed ethnicity identification was tested using several classification algorithms. From the experimental result, we achieved a better result in multi-color feature compared to individual color space model under Random Forest algorithm.</span>

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Tchebichef image watermarking along the edge using YCoCg-R color space for copyright protection

Cited by 21 publications

References 17 publications

An Image Watermarking Method Using Discrete Tchebichef Transform and Singular Value Decomposition Based on Chaos Embedding

An Image Watermarking Method Using Discrete Tchebichef Transform and Singular Value Decomposition Based on Chaos Embedding

Multiple watermarking technique using optimal threshold

A multi-color based features from facial images for automatic ethnicity identification model

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