Shishu Bind Kumar

Bio: Shishu Bind Kumar is an academic researcher from Motilal Nehru National Institute of Technology Allahabad. The author has contributed to research in topic(s): Error detection and correction & Histogram equalization. The author has an hindex of 2, co-authored 2 publication(s) receiving 29 citation(s).

Wavelet based imperceptible medical image watermarking using spread-spectrum

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.

Development of improved SSIM quality index for compressed medical images

Abstract: This paper presents the development of improved structural similarity index (SSIM) quality assessment parameter for compressed medical images. The SSIM has been proved to be better objective quality assessment metric which exploits the structural similarity in the viewing field. In this paper, the SSIM quality index has been modified by achieving optimal value of arbitrary constant K used in SSIM index expression. The analysis has been done for three different types of medical image; MRI scan, CT scan and ultrasound image. SSIM index along with PSNR, MSE and mean-opinion-score (MOS) are computed for SPIHT compressed medical images at varying compression rates by setting values of K in the range 0.02 to 2.0. The value of K giving maximum correlation coefficient (CC) between SSIM index and MOS is selected as optimal value. It is found that optimal values of K equal to 0.5, 0.05 and 0.1 for MRI, CT scan and ultrasound images respectively.

Robust and Imperceptible Dual Watermarking for Telemedicine Applications

Abstract: In this paper, the effects of different error correction codes on the robustness and imperceptibility of discrete wavelet transform and singular value decomposition based dual watermarking scheme is investigated. Text and image watermarks are embedded into cover radiological image for their potential application in secure and compact medical data transmission. Four different error correcting codes such as Hamming, the Bose, Ray-Chaudhuri, Hocquenghem (BCH), the Reed---Solomon and hybrid error correcting (BCH and repetition code) codes are considered for encoding of text watermark in order to achieve additional robustness for sensitive text data such as patient identification code. Performance of the proposed algorithm is evaluated against number of signal processing attacks by varying the strength of watermarking and covers image modalities. The experimental results demonstrate that this algorithm provides better robustness without affecting the quality of watermarked image.This algorithm combines the advantages and removes the disadvantages of the two transform techniques. Out of the three error correcting codes tested, it has been found that Reed---Solomon shows the best performance. Further, a hybrid model of two of the error correcting codes (BCH and repetition code) is concatenated and implemented. It is found that the hybrid code achieves better results in terms of robustness. This paper provides a detailed analysis of the obtained experimental results.

Anatomical-Functional Image Fusion by Information of Interest in Local Laplacian Filtering Domain

Abstract: A novel method for performing anatomical magnetic resonance imaging-functional (positron emission tomography or single photon emission computed tomography) image fusion is presented. The method merges specific feature information from input image signals of a single or multiple medical imaging modalities into a single fused image, while preserving more information and generating less distortion. The proposed method uses a local Laplacian filtering-based technique realized through a novel multi-scale system architecture. First, the input images are generated in a multi-scale image representation and are processed using local Laplacian filtering. Second, at each scale, the decomposed images are combined to produce fused approximate images using a local energy maximum scheme and produce the fused residual images using an information of interest-based scheme. Finally, a fused image is obtained using a reconstruction process that is analogous to that of conventional Laplacian pyramid transform. Experimental results computed using individual multi-scale analysis-based decomposition schemes or fusion rules clearly demonstrate the superiority of the proposed method through subjective observation as well as objective metrics. Furthermore, the proposed method can obtain better performance, compared with the state-of-the-art fusion methods.

Robust and Secure Multiple Watermarking for Medical Images

Abstract: This paper presents a robust and secure region of interest and non-region of interest based watermarking method for medical images. The proposed method applies the combination of discrete wavelet transform and discrete cosine transforms on the cover medical image for the embedding of image and electronic patient records (EPR) watermark simultaneously. The embedding of multiple watermarks at the same time provides extra level of security and important for the patient identity verification purpose. Further, security of the image and EPR watermarks is enhancing by using message-digest (MD5) hash algorithm and Rivest---Shamir---Adleman respectively before embedding into the medical cover image. In addition, Hamming error correction code is applying on the encrypted EPR watermark to enhance the robustness and reduce the possibility bit error rates which may result into wrong diagnosis in medical environments. The robustness of the method is also extensively examined for known attacks such as salt & pepper, Gaussian, speckle, JPEG compression, filtering, histogram equalization. The method is found to be robust for hidden watermark at acceptable quality of the watermarked image. Therefore, the hybrid method is suitable for avoidance of the patient identity theft/alteration/modification and secure medical document dissemination over the open channel for medical applications.

Multilevel Encrypted Text Watermarking on Medical Images Using Spread-Spectrum in DWT Domain

Abstract: This paper presents a secure multilevel watermarking scheme in which the encrypted text acts as a watermark. The algorithm is based on secure spread-spectrum technique for digital images in discrete wavelet transform (DWT) domain. Potential application of the proposed watermarking scheme is successfully demonstrated for embedding various medical watermarks in text format at different subband decomposition levels depending upon their performance requirements. In the embedding process, the cover CT Scan image is decomposed up to third level of DWT coefficients. Different text watermarks such as personal and medical record of the patient, diagnostic/image codes and doctor code/signature are embedded into the selective coefficients of the second and third level DWT for potential telemedicine applications. Selection of DWT coefficients for embedding is done by column wise thresholding of coefficients values. Also, encryption is applied to the ASCII representation of the text and the encoded text watermark is embedded. The algorithm correctly extracts the embedded watermarks without error and is robust against numerous known attacks without much degradation of the medical image quality of the watermarked image.

Quantization based multiple medical information watermarking for secure e-health

Abstract: In this paper, an improved wavelet based medical image watermarking algorithm is proposed. Initially, the proposed technique decomposes the cover medical image into ROI and NROI regions and embedding three different watermarks into the non-region of interest (NROI) part of the transformed DWT cover image for compact and secure medical data transmission in E-health environment. In addition, the method addressing the problem of channel noise distortion may lead to faulty watermark by applying error correcting codes (ECCs) before embedding them into the cover image. Further, the bit error rates (BER) performance of the proposed method is determined for different kind of attacks including ‘Checkmark’ attacks. Experimental results indicate that the Turbo code performs better than BCH (Bose-Chaudhuri-Hochquenghem) error correction code. Furthermore, the experimental results validate the effectiveness of the proposed framework in terms of BER and embedding capacity compared to other state-of-the-art methods. Therefore, the proposed method finds potential application in prevention of patient identity theft in e-health applications.