Wavelet based imperceptible medical image watermarking using spread-spectrum
09 Jul 2015-pp 1-5
TL;DR: A spread-spectrum watermarking algorithm for embedding text watermark in to digital images in discrete wavelet transform (DWT) domain and it is observed that the use of BCH code improves the performance by reducing bit error rate (BER) performance.
Abstract: This paper presents a spread-spectrum watermarking algorithm for embedding text watermark in to digital images in discrete wavelet transform (DWT) domain. The algorithm is applied for embedding text file represented in binary arrays using ASCII code into host digital radiological image for potential telemedicine applications. In order to enhance the robustness of text watermarks like patient identity code, BCH (Bose, Ray-Chaudhuri, Hocquenghem) error correcting code (ECC) is applied to the ASCII representation of the text watermark before embedding. Performance of the algorithm is analysed by varying the gain factor, subband decomposition levels, and length of watermark. Robustness of the scheme is tested against various attacks like compression, filtering, noise, sharpening, scaling and histogram equalization. Simulation results show that the proposed method achieves imperceptible watermarking for string watermarks. It is also observed that the use of BCH code improves the performance by reducing bit error rate (BER) performance.
Citations
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TL;DR: Using least significant bits (LSB) to hide important information in fingerprint images and chaotic sequence encryption (CSE) to securely transmit useful data and shows that Chameleon can resist static attacks and protect the privacy of users regarding to the information security and integrity.
Abstract: Recently, in a variety of Internet of Things (IoT) application scenarios, fingerprint image as a common biological information has been widely collected. For example, in safe city projects, civil fingerprints representing unique identification are vastly assembled, stored, and transmitted wirelessly. Under such situations, data privacy protection becomes increasingly valued. In our study, this fundamental problem was centered. In our work, the method to remain secure in such an universal cloud based IoT system and the approach to hide important information in biologically collected data such are fully discussed. A new lightweight algorithm in protecting the privacy and integrity of data in a cloud based IoT system is badly needed. We believe that it is a way to hide the core information in the surrounding environment just like “Chameleon” to protect the data security. Thus, in this paper, we propose “CHAMELEON” by using least significant bits (LSB) to hide important information in fingerprint images and chaotic sequence encryption (CSE) to securely transmit useful data. The experimental results of this algorithm show that Chameleon can resist static attacks and protect the privacy of users regarding to the information security and integrity.
3 citations
01 Jan 2019
TL;DR: This chapter proposes a new sparse domain image watermarking system that gives strength against different sorts of image processing attacks in term of normalized correlation (NC), and guarantees security to cover picture and is safe against different water marking attacks.
Abstract: The biomedical images and biometric images is composed of vital wellbeing data, critical unique identity and conduct data of human. Hence, pictures identified with these two data types must be kept secret and must be secured over transmission medium. In this chapter, a new sparse domain image watermarking is proposed, performance examined and correlated with the existing watermarking systems. The proposed technique utilizes the sparsity property of Discrete Wavelet Transform (DWT) and Compressive Sensing (CS) hypothesis procedure to accomplish high strength and security. This technique hides secret watermark data into encoded cover image rather than the frequency coefficients of the original cover image. The scrambled cover image is created from CS hypothesis. In this method, different kinds of biomedical images and ear biometric image are used as cover images and a binary logo is utilized as watermark. The logo is implanted into sparse measurements of cover image using noise sequences and constant gain factor to achieve blind extraction of watermark image. The CS hypothesis guarantees security to cover picture and is safe against different watermarking attacks. Exploratory outcomes demonstrated that the proposed system gives strength against different sorts of image processing attacks in term of normalized correlation (NC).
2 citations
01 Jan 2019
TL;DR: This chapter presents various data hiding techniques for security of medical image designed using various image transforms such as FDCuT, DCT, FRT, NSCT, and various encryption methods such as Arnold scrambling and compressive sensing (CS) theory.
Abstract: This chapter presents various data hiding techniques for security of medical image. These techniques are designed using various image transforms such as FDCuT, DCT, FRT, NSCT, and various encryption methods such as Arnold scrambling and compressive sensing (CS) theory. Finally, simulation results of these techniques are demonstrated in this chapter.
TL;DR: A new cooperative spread spectrum based blind watermarking technique, which can apply to not only single channel images but also multi-channel images or set of images, and the optimal solutions of the watermark, watermark strength coefficients, weighting coefficients, threshold, and probability error are established.
Abstract: Spread Spectrum (SS) is one of the most common techniques used in watermarking systems due to its security, robustness, imperceptibility and information extracting without the host data. However, this technique suffers the interference between the host data and the watermark, which degrades significantly the performance of watermarking system. In the other hand, most existing spread spectrum-based image watermarking methods are non-blind and implemented for single channel images with one information bit. Therefore, this paper presents a new cooperative spread spectrum based blind watermarking technique, which can apply to not only single channel images but also multi-channel images or set of images. In this technique, the same information is embedded into multiple channels and a global linear cooperative decision is used to exploit the collaboration among the local correlation detectors. Moreover, improved method is also mentioned to eliminate the interference between the host images and the watermarks. Especially, the Karhunen Loeve Transform (KLT) is exploited to enhance the performance of the proposed cooperative watermarking system. Furthermore, extensive methods for multi-bit watermarking are also discussed. Based on theoretical analysis, the optimal solutions of the watermark, watermark strength coefficients, weighting coefficients, threshold, and probability error are established. Experimental results are simulated with ideal channel (without attack) as well as additive Gaussian channel to verify theoretical analysis.
Cites background or methods from "Wavelet based imperceptible medical..."
...Because of these characteristics, the spread spectrum based watermarking is still being researched and developed in many applications [7]-[14]....
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...In addition, spread spectrum based watermarking techniques can be implemented directly in the spatial domain or other transform domains such as DFT, DCT or DWT in order to improve the robustness against attacks [3], [14]....
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TL;DR: An efficient blind robust watermarking solution for medical images based on a combination of the Scale Invariant Feature Transform (SIFT) and even-odd quantization that can extract the embedded information without original image by selecting only non-overlapping features in embedding process and exploiting the correlation among all detecting regions.
Abstract: The paper proposes an efficient blind robust watermarking solution for medical images based on a combination of the Scale Invariant Feature Transform (SIFT) and even-odd quantization. Unlike most existing methods using SIFT with original image, our proposed algorithm can extract the embedded information without original image by selecting only non-overlapping features in embedding process and exploiting the correlation among all detecting regions. As a result, both detection and extraction of embedded information can be obtained with our method. Moreover, it can be expanded to multi-bit watermarking with two suggestions of fan-shaped and half-ring-shaped regions. The experimental results are implemented with various medical images and evaluated about the quality, the reliability and the robustness against common medical image processing attacks including filtering, compression, rotation, scaling and cropping. Furthermore, the security in embedding and extracting information is also enhanced in our solution.
References
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TL;DR: It is argued that insertion of a watermark under this regime makes the watermark robust to signal processing operations and common geometric transformations provided that the original image is available and that it can be successfully registered against the transformed watermarked image.
Abstract: This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data. We advocate that a watermark should be constructed as an independent and identically distributed (i.i.d.) Gaussian random vector that is imperceptibly inserted in a spread-spectrum-like fashion into the perceptually most significant spectral components of the data. We argue that insertion of a watermark under this regime makes the watermark robust to signal processing operations (such as lossy compression, filtering, digital-analog and analog-digital conversion, requantization, etc.), and common geometric transformations (such as cropping, scaling, translation, and rotation) provided that the original image is available and that it can be successfully registered against the transformed watermarked image. In these cases, the watermark detector unambiguously identifies the owner. Further, the use of Gaussian noise, ensures strong resilience to multiple-document, or collusional, attacks. Experimental results are provided to support these claims, along with an exposition of pending open problems.
6,194 citations
"Wavelet based imperceptible medical..." refers background in this paper
...The problem of watermark security can be solved using spread-spectrum scheme [14]-[16]....
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TL;DR: The authors begin by discussing the need for watermarking and the requirements and go on to discuss digitalWatermarking techniques based on correlation and techniques that are notbased on correlation.
Abstract: The authors begin by discussing the need for watermarking and the requirements. They go on to discuss digital watermarking techniques based on correlation and techniques that are not based on correlation.
789 citations
"Wavelet based imperceptible medical..." refers methods in this paper
...General watermarking method needs to keep the three factors (capacity, imperceptibility and robustness) reasonably very high [4]....
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TL;DR: The proposed ISS is as robust in practice as traditional SS, and achieves roughly the same noise robustness gain as quantization index modulation (QIM) but without the amplitude scale sensitivity of QIM.
Abstract: This paper introduces a new watermarking modulation technique, which we call improved spread spectrum (ISS). When compared with traditional spread spectrum (SS), the signal does not act as a noise source, leading to significant gains. In some examples, performance improvements over SS are 20 dB in signal-to-noise ratio (SNR) or ten or more orders of magnitude in the error probability. The proposed method achieves roughly the same noise robustness gain as quantization index modulation (QIM) but without the amplitude scale sensitivity of QIM. Our proposed ISS is as robust in practice as traditional SS.
499 citations
TL;DR: An overview of wavelet-based watermarking techniques available today can be found in this paper, where the authors provide an overview of the wavelet wavelet transform domain and its application in image compression.
Abstract: In this paper, we will provide an overview of the wavelet-based watermarking techniques available today. We will see how previously proposed methods such as spread-spectrum watermarking have been applied to the wavelet transform domain in a variety of ways and how new concepts such as the multi-resolution property of the wavelet image decomposition can be exploited. One of the main advantages of watermarking in the wavelet domain is its compatibility with the upcoming image coding standard, JPEG2000. Although many wavelet-domain watermarking techniques have been proposed, only few fit the independent block coding approach of JPEG2000. We will illustrate how different watermarking techniques relate to image compression and examine the robustness of selected watermarking algorithms against image compression.
302 citations
01 Oct 2006
TL;DR: Experimental results indicate the efficiency and transparency of the scheme, which conforms to the strict requirements that apply to regions of diagnostic significance.
Abstract: Information technology advances have brought forth new challenges in healthcare information management, due to the vast amount of medical data that needs to be efficiently stored, retrieved, and distributed, and the increased security threats that explicitly have to be addressed. The paper discusses the perspectives of digital watermarking in a range of medical data management and distribution issues, and proposes a complementary and/or alternative tool that simultaneously addresses medical data protection, archiving, and retrieval, as well as source and data authentication. The scheme imperceptibly embeds in medical images multiple watermarks conveying patient's personal and examination data, keywords for information retrieval, the physician's digital signature for authentication, and a reference message for data integrity control. Experimental results indicate the efficiency and transparency of the scheme, which conforms to the strict requirements that apply to regions of diagnostic significance
203 citations