Robust and Secure Multiple Watermarking for Medical Images

Sharma, Abhilasha; Singh, Amit Kumar; Ghrera, Satya Prakash

doi:10.1007/s11277-016-3625-x

Cited by 68 publications

(21 citation statements)

References 23 publications

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“…The maximum NC value obtained at scaling factor= 0.2 is 1 for watermark image 'Doctor image' against Gaussian noise compared to 0.9908obtained by [2], 0.9466 obtained by [3] and 0.944001 obtained by [10] respectively, 1 for watermark image 'Doctor image' against Salt & pepper compared to 0.9953obtained by [2], 0.9658obtained by [3] and 0.949754obtained by [10] respectively, 1 for watermark images 'Doctor image' and 'Fingerprint' against Speckle noise (density = 0.00001)compared to 0.949742obtained by [10], 1 for watermark image 'Doctor image' against Median filtering compared to 0.9861 obtained by [2], 0.0123 obtained by [3] and 0.9985 obtained by [10] respectively, 1 for watermark image 'Doctor image' against Salt & Peppers (d = 0.002) + Speckle (V=0.005) compared to 0.8328 obtained by [3], and finally 1 for watermark image 'Doctor image' against Gaussian (M=0.01,V=0.002)+ Speckle (V=0.005)compared to 0.8276 obtained by [3].…”

Section: T R a N S A C T I O N S O N M A C H I N E L E A R N I N G A mentioning

confidence: 82%

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Robust Multiple Watermarking Technique for Medical Applications using DWT, DCT and SVD

Assini

Badri

Safi

et al. 2017

TMLAI

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The security of medical data plays an important role in preserving their integrity and confidentiality. This paper presents a robust multiple watermarking algorithm based on a combination of discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD).In this proposed method, we have inserted three watermark images (a patient image, a doctor image and a fingerprint of the patient) into a single cover medical image. In the insertion phase, the original image is decomposed into the third level of DWT, and then the DCT and SVD transforms are applied on the selected sub bands (HH1, HH2, and HH3). The first watermark goes through the same steps that the original image. Moreover, the second and the third watermarks are decomposed until the second level and the first level by DWT respectively and subsequently transformed by SVD. The singular values of the three watermarks are inserted into the singular values of the original image. The experimental results show that the proposed method gives better performance in terms of capacity, quality and robustness against various attacks compared to other reported techniques.

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Section: T R a N S A C T I O N S O N M A C H I N E L E A R N I N G A mentioning

confidence: 82%

“…However, the minimum NC value is 0.9571 against Speckle noise for watermark image 'Fingerprint'. In Table 5, we have compared the robustness of our technique against various attacks compared to existing techniques [2], [3] and [10].…”

Section: T R a N S A C T I O N S O N M A C H I N E L E A R N I N G A mentioning

confidence: 99%

Robust Multiple Watermarking Technique for Medical Applications using DWT, DCT and SVD

Assini

Badri

Safi

et al. 2017

TMLAI

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“…Durante los últimos años se han implementado técnicas basadas en marcas de agua, las cuales son aplicadas a imágenes médicas [7][8][9][10][11][12][13]. En la presente sección se presentan los métodos más representativos los cuales aplican técnicas de marcado de agua en imágenes médicas.…”

Section: Estado Del Arteunclassified

“…Sharma [9] propone marca de agua múltiple combinando las transformadas DWT y la Transformada Discreta del Coseno (DCT por sus siglas en inglés de Discrete Cosine Transform), además de los algoritmos de cifrado RSA (Rivest, Shamir y Adleman) y MD5 (Message-Digest Algorithm 5), y el ECC Hamming, en este proceso utiliza dos marcas de agua, una imagen (logo del centro hospitalario) y otra marca de agua como texto (EPR) los cuales son cifrados por el algoritmo RSA.…”

Section: Estado Del Arteunclassified

“…La protección de información médica en la mayoría de los países se deriva de una estricta regulación como la HIPAA de los Estados Unidos y la Directiva Europea de la CE 95/46 que aplica a los registros de información de un paciente, los cuales contienen un conjunto exámenes clínicos, anotaciones de diagnósticos y otros hallazgos e imágenes en los EPR [5], Así mismo se tiene la norma de protección de datos personales en salud en México: NOM-004-SSA3-2012 [6]. Debido a lo anterior, son necesarios métodos que se utilicen para la protección de datos del paciente, una solución a esto son las marcas de agua [9,[12][13][14], las cuales son técnicas empleadas para insertar un mensaje o contenido digital dentro de otro archivo digital (denominado archivo host), estas técnicas son utilizadas para aumentar el nivel de seguridad y/o autenticidad del archivo host multimedia.…”

Section: Introductionunclassified

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Mejora de un esquema de marca de agua aplicado a la gestión de imágenes médicas

Lagunas¹,

Molina‐García²,

Ponomaryov³

2018

RCS

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En el presente trabajo se propone un método de marca de agua basado en la DWT que aborda los problemas de protección de datos personales y datos sobre los estudios clínicos de un paciente, recuperación de datos del médico que lleva a cabo los estudios y verificación de la integridad de las imágenes médicas. El esquema de marcado realiza la descomposición de una imagen médica en formato DICOM al dominio tiempo-frecuencia mediante la DWT, insertado bits empleados para detección de alteraciones en el primer nivel de descomposición de la sub-banda HL, posteriormente se inserta la información del paciente, identificación del médico e información adicional empleada durante la extracción en la sub-banda de frecuencia LH. Los resultados obtenidos muestran que las imágenes protegidas no se degradan de manera significativa, ya que se obtiene un valor en términos de PSNR (dB) superior a 50dB; asimismo, se demostró que el esquema de marcado de agua es capaz de extraer la información insertada empleando ataques no intencionales como compresión. Finalmente, se mostró experimentalmente la eficiencia del método propuesto para detectar alteraciones empleando ataques de adición de ruido y emborronamiento. Palabras clave: marcas de agua, imágenes médicas, confidencialidad, detección de alteraciones, gestión de imágenes médicas.

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SPIHT‐based multiple image watermarking in NSCT domain

Kumar

Singh

Kumar

et al. 2018

Concurrency and Computation

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Image watermarking in wavelet domain is a challenging problem as it includes a proper selection of wavelet transforms as well as sub-bands for accurate embedding and recovery of watermarks.However, selection of a suitable wavelet transform for multiple image watermarking is an area of great interest. Therefore, in this work, a multiple watermarking technique using combination of redundant discrete wavelet transforms (RDWT), non-subsampled contourlet transform (NSCT), set partitioning in hierarchical tree (SPIHT), and singular value decomposition (SVD) is proposed. The proposed scheme is aimed to achieve high capacity, robustness, and imperceptibility. The security aspect of the proposed method is enhanced by using Arnold transform. Since RDWT and NSCT are both shift invariant in nature, therefore they are suitable for multiple image watermarking. Furthermore, the proposed method provides flexibility in selection of appropriate sub-bands for watermark embedding and recovery. Experimental results and analysis reveals that the proposed technique gives maximum PSNR, NC, and SSIM value up to 40.97 dB, 1, and 0.9994, respectively. Furthermore, the performance estimation of our technique is found superior to previously reported techniques under consideration. KEYWORDSArnold transform, non-sub sampled contourlet transform, RDWT, SPIHT, SVD INTRODUCTIONRecently, secure transmission of digital data over open/public networks is one of potential challenges. 1 Therefore, there is a great requirement to secure the data transmission over networks. Digital image watermarking is one of promising method for protecting digital data and is widely used for copyright protection and secure communication. 2-4 Image watermarking provides secure transmission of digital data by embedding it into the cover image for content authentications, copyright protection, 5 etc.Discrete wavelet transform (DWT) has been widely used for image watermarking. 6 However, the major drawbacks associated with the DWT are its shift sensitivity and poor directionality that can be avoided by using redundant wavelet transforms. 7 The existing literatures over image watermarking clearly states that the redundant wavelet transforms are suitable for single and multiple images watermarking 7-10 as these transforms do not use down sampling operation in implementation. Thus, no data/information loss occurs during forward and inverse transformation. Furthermore, redundant discrete wavelet transform (RDWT) 11 and non-subsampled contourlet transform (NSCT) 12 are shift invariant. This property enables us to have better reconstruction of images and found useful in many image processing applications. Furthermore, NSCT provides rich directional information, which can be used in embedding single as well as multiple watermarks after forward transformation. 12 It is evident that the performance of combined transform domain techniques (two or more than two) is better than individual one. 7 Thus, being motivated by above facts, an image watermarking technique in NSCT domain using...

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Robust and Secure Multiple Watermarking for Medical Images

Cited by 68 publications

References 23 publications

Robust Multiple Watermarking Technique for Medical Applications using DWT, DCT and SVD

Robust Multiple Watermarking Technique for Medical Applications using DWT, DCT and SVD

Mejora de un esquema de marca de agua aplicado a la gestión de imágenes médicas

SPIHT‐based multiple image watermarking in NSCT domain

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