An evolutionary programming approach for securing medical images using watermarking scheme in invariant discrete wavelet transformation. (May 2018)

• Record Type: Journal Article
• Authors: Gangadhar, Y.; Giridhar Akula, V.S.; Reddy, P. Chenna
• Is Part Of: Biomedical signal processing and control. Volume 43(2018)
• Page Start: 31
• Page End: 40
• Publication Date: 2018-05
• Subjects: Watermarking -- Scalability -- Particle swarm optimization -- Authentication -- Normalized coefficient; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2018.02.007
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: The proposed watermarking scheme utilized improved discrete wavelet transformation (IDWT) to retrieve the invariant wavelet domain. The entropy mechanism is used to identify the suitable region for insertion of watermark. This will improve the imperceptibility and robustness of the watermarking procedure. The scaling factors such as PSNR and NC are considered for evaluation of the proposed method and the Particle Swarm Optimization is employed to optimize the scaling factors. Abstract: The importance of digital images in the field of health care made major impact in the recent years. There is need for protecting the medical images from unauthorized usage and watermarking serves well in this situations. Digital medical Image watermarking is the procedure of protecting the medical image content by inserting the watermark into it. The major objective of the image watermarking technique is to develop an algorithm with high imperceptibility. To achieve this, this paper proposed the image watermarking algorithm in wavelet transformation (IDWT) using the singular value decomposition (SVD) and particle swarm optimization (PSO). The improved DWT is applied to the medical image to retrieve the invariant wavelet domain. The watermark is inserted in to the selected region by modifying the values of the coefficients in the image using threshold function. The scaling factors are optimized using the PSO algorithm. The performance of the proposed model is evaluated using the existing schemes similar to the properties of the proposed model. The normalized coefficient (NC) and Peak Signal to Noise Ratio (PSNR) is considered to evaluate the similarity between the medical image and watermarked medical image. The proposed algorithm showed improved performance in terms of imperceptibility and robustness.