Wavelet transform and pixel strength-based robust watermarking using dragonflyoptimization

The exponential growth of the information technology has created a pathetic panorama in the field of Health Information System (HIS) that draws the attention of the researchers. Watermarking is a trending topic that provides security to the encapsulated secret code in the medical image and hence, ensures security to the medical images and contributes towards efficient information extraction. The images arelikely to be attacked by intruders, which may be intentional or accidental attack of noises. Therefore, the verification of the image and its related data is necessary.Keeping the security and distortion free watermarking as an objective, this paper proposes a robust watermarking approach that depends upon weight of the pixels. The image makes use of DWT to extract the high and the low frequency bands to select the effective pixels for watermarking. The dragonfly optimization determines the effective pixel that follows the objective function based on ENeGW (Edge level, Neighbourhood strength, Gradient energy, and Wavelet energy) of the pixel. Experimentation is rendered on medical retinal image using patient data as a watermark, and the comparative study is made on the suggested watermarking procedure with the existing methods, such as random selection, PSO, and genetic algorithm. The comparative performance analysis is done and its outcome shows the supremacy of the suggested methodology.