Title: Effect of trigonometric functions-based watermarking on blood vessel extraction: an application in ophthalmology imaging
Authors: Nilanjan Dey; Sk. Saddam Ahmed; Sayan Chakraborty; Prasenjit Maji; Achintya Das; Sheli Sinha Chaudhuri
Addresses: Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, West Bengal, India ' Department of Computer Science and Engineering, JIS College of Engineering, Kalyani, West Bengal, India ' Department of Computer Science and Engineering, Bengal College of Engineering and Technology, Durgapur, West Bengal, India ' Department of Computer Science and Engineering, Bengal College of Engineering and Technology, Durgapur, West Bengal, India ' Department of Electronics and Communication Engineering, Kalyani Govt. Engineering College, Kalyani, West Bengal, India ' Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, West Bengal, India
Abstract: With the growth of globalisation, security has been a major concern in digital exchange of medical information. Data hiding, also referred as watermarking, was introduced to authenticate medical data which is sent over the network. Watermarking of electronic patient reports (EPR) for telemedicine demands robust, imperceptible, high payload techniques. Blood vessel extraction is mainly used for diabetic retinopathy (DR) for automatic extraction and classification of severity of diseases. In our current work, blood vessel from fundus images is extracted using K-means segmentation. Afterwards, EPR is hidden using interpolation and trigonometric functions in fundus image. Finally, blood vessel is extracted from the watermarked image to measure the changes in accuracy of the proposed system. The percentage difference (< 0.25%) of accuracy in fundus images before watermarking and after watermarking claims the retention of devalorisation of vessel extraction accuracy measurement. High peak signal to noise ratio (PSNR) value (> 36) and high correlation (> 87%) between original and watermarked retinal image, establishes the robustness of the proposed non-blind watermarking method.
Keywords: blood vessel extraction; non-blind watermarking; electronic patient records; EPR; K-means clustering; peak SNR; signal to noise ratio; PSNR; trigonometric functions; ophthalmology imaging; information security; medical information; data hiding; telemedicine; diabetic retinopathy; disease severity; fundus images; image segmentation; interpolation; image security; retinal images; diabetes.
International Journal of Embedded Systems, 2017 Vol.9 No.1, pp.90 - 100
Available online: 20 Jan 2017 *Full-text access for editors Access for subscribers Purchase this article Comment on this article