A Color-Texture Image Watermarking Algorithm Based on Texture Analysis (텍스처 분석 기반 칼라 텍스처 이미지 워터마킹 알고리즘)

강명수; Truc Kim Thi Nguyen (트룩뉘엔); Dinh Van Nguyen (딘뉘엔); Cheol Hong Kim (김철홍); Jong Myon Kim (김종면)

A Color-Texture Image Watermarking Algorithm Based on Texture Analysis

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2013, 18(4), pp.35-43
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science

강명수 ¹, Truc Kim Thi Nguyen ¹, Dinh Van Nguyen ¹, Cheol Hong Kim ², Jong Myon Kim ¹

¹울산대학교
²전남대학교

Accredited

ABSTRACT

As texture images have become prevalent throughout a variety of industrial applications,copyright protection of these images has become important issues. For this reason, this paper proposes a color-texture image watermarking algorithm utilizing texture properties inherent in the image. The proposed algorithm selects suitable blocks to embed a watermark using the energy and homogeneity properties of the grey level co-occurrence matrices as inputs for the fuzzy c-means clustering algorithm. To embed the watermark, we first perform a discrete wavelet transform (DWT) on the selected blocks and choose one of DWT subbands. Then, we embed the watermark into discrete cosine transformed blocks with a gain factor. In this study, we also explore the effects of the DWT subbands and gain factors with respect to the imperceptibility and robustness against various watermarking attacks. Experimental results show that the proposed algorithm achieves higher peak signal-to-noise ratio values (47.66 dB to 48.04 dB) and lower M-SVD values (8.84 to 15.6) when we embedded a watermark into the HH band with a gain factor of 42, which means the proposed algorithm is good enough in terms of imperceptibility. In addition, the proposed algorithm guarantees robustness against various image processing attacks, such as noise addition, filtering,cropping, and JPEG compression yielding higher normalized correlation values (0.7193 to 1).

KEYWORDS

Texture image watermarking, Grey level co-occurrence matrices, Fuzzy c-means clustering, Discrete wavelet transform, Discrete cosine transform

Citation status

* References for papers published after 2023 are currently being built.

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This paper was written with support from the National Research Foundation of Korea.

KJCKorea
Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65