“…For data hiding in encrypted domain, also including both spatial domain and transform domain, the original image is first encrypted and then watermarked. Data hiding in spatial domain was conducted in [12][13][14][15][16], while authors of [17,18] hide data in transform domain.…”
This paper proposes a novel tamper detection, localization, and recovery scheme for encrypted images with Discrete Wavelet Transformation (DWT) and Compressive Sensing (CS). The original image is first transformed into DWT domain and divided into important part, that is, low-frequency part, and unimportant part, that is, high-frequency part. For low-frequency part contains the main information of image, traditional chaotic encryption is employed. Then, high-frequency part is encrypted with CS to vacate space for watermark. The scheme takes the processed original image content as watermark, from which the characteristic digest values are generated. Comparing with the existing image authentication algorithms, the proposed scheme can realize not only tamper detection and localization but also tamper recovery. Moreover, tamper recovery is based on block division and the recovery accuracy varies with the contents that are possibly tampered. If either the watermark or low-frequency part is tampered, the recovery accuracy is 100%. The experimental results show that the scheme can not only distinguish the type of tamper and find the tampered blocks but also recover the main information of the original image. With great robustness and security, the scheme can adequately meet the need of secure image transmission under unreliable conditions.
“…For data hiding in encrypted domain, also including both spatial domain and transform domain, the original image is first encrypted and then watermarked. Data hiding in spatial domain was conducted in [12][13][14][15][16], while authors of [17,18] hide data in transform domain.…”
This paper proposes a novel tamper detection, localization, and recovery scheme for encrypted images with Discrete Wavelet Transformation (DWT) and Compressive Sensing (CS). The original image is first transformed into DWT domain and divided into important part, that is, low-frequency part, and unimportant part, that is, high-frequency part. For low-frequency part contains the main information of image, traditional chaotic encryption is employed. Then, high-frequency part is encrypted with CS to vacate space for watermark. The scheme takes the processed original image content as watermark, from which the characteristic digest values are generated. Comparing with the existing image authentication algorithms, the proposed scheme can realize not only tamper detection and localization but also tamper recovery. Moreover, tamper recovery is based on block division and the recovery accuracy varies with the contents that are possibly tampered. If either the watermark or low-frequency part is tampered, the recovery accuracy is 100%. The experimental results show that the scheme can not only distinguish the type of tamper and find the tampered blocks but also recover the main information of the original image. With great robustness and security, the scheme can adequately meet the need of secure image transmission under unreliable conditions.
“…(Kalra, Talwar, & Sadawarti, 2015;Laptev, Caputo, Schuldt, & Lindeberg, 2007;Liu, Wang, & Zhu, 2015). The video sequence can be regarded as a 3D space-time function.…”
Section: D-harris Algorithm Spatio-temporal Interest Point Detectionmentioning
Digital video is vulnerable to accidental or malicious destruction in storage, transmission, processing, which damages the legitimate rights and interests of the product owners. Digital video watermarking technology is a mean to protect intellectual property rights. We analyze the basic principle of the 3D-Harris algorithm and Gabor filter method. By considering the temporal causality of the video, the common symmetrical filter is discarded. We design a causal filter which conforms to video characteristics and proposes an asymmetric causal filter in space-time domain. On this basis, an improved video watermarking algorithm is proposed, combining space-time feature points and DCT domain. The experimental results show that proposed algorithm can not only ensure high invisibility, and can effectively resist various attacks in time domain and space domain.
ARTICLE HISTORY
“…Watermark embedding can be performed in different transform domains including DWT (Singh and Singh, 2016;Bhatnagar et al, 2012;Mishra et al, 2014;Priyanka and Maheshkar, 2016), DCT (Priyanka and Maheshkar, 2016;Roy and Pal, 2017;Kalra et al, 2015;Takore et al, 2016), SVD (Shah et al, 2015;Priyanka and Maheshkar, 2016;Hu and Hsu, 2015) and others (Chen et al, 2014;Cedillo et al, 2014). Preda and Vizireanu (2015) devised an image authentication scheme which works in DCT domain.…”
This paper presents a new robust and invisible blind watermarking approach of colour images for copyright protection in hybrid DWT-DCT-SVD domain. In the proposed method, firstly the luminance component (Y) of the cover image is decomposed up to one level of discrete wavelet transform (DWT) coefficients and the low frequency band (LL) is transformed by discrete cosine transform (DCT). Then several selected low and intermediate frequency DCT coefficients of each block are extracted to generate a feature matrix and singular value decomposition (SVD) transform is applied to the feature matrix. Finally the watermark information is embedded by modifying the singular values of the feature matrix. Experimental results demonstrate that the proposed approach outperforms some popular existing watermarking methods in robustness against median filtering, Gaussian filtering, salt and pepper noise, average filtering, Gaussian noise, histogram equalisation, and so on, especially in case of lossy JPEG compression in addition to good imperceptibility.
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