Anamitra Bardhan Roy

A Novel Approach of Color Image Hiding using RGB Color planes and DWT

This work proposes a wavelet based Steganographic technique for the color image. The true color cover image and the true color secret image both are decomposed into three separate color planes namely R, G and B. Each plane of the images is decomposed into four sub bands using DWT. Each color plane of the secret image is hidden by alpha blending technique in the corresponding sub bands of the respective color planes of the original image. During embedding, secret image is dispersed within the original image depending upon the alpha value. Extraction of the secret image varies according to the alpha value. In this approach the stego image generated is of acceptable level of imperceptibility and distortion compared to the cover image and the overall security is high.

DWT-DCT-SVD based blind watermarking technique of gray image in electrooculogram signal

At present most of the hospitals and diagnostic centers globally, use wireless media to exchange biomedical information for mutual availability of therapeutic case studies. The required level of security and authenticity for transmitting biomedical information through the internet is quite high. Level of security can be increased; authenticity of the information can be verified and control over the copy process can be ascertained by adding watermark as “ownership” information in multimedia content. In this proposed method different types of gray scale biomedical images can be used as added ownership (watermark) data. Electrooculography is a medical test used by the ophthalmologists for monitoring eyeball movement in Rapid Eye Movement (REM) and non-REM sleep, to detect the disorders of human eyes and to measure the resting potential of the eye. In this present work 1-D EOG signal is transformed into 2-D signal. DWT, DCT, SVD are applied on the transformed 2D signal to embed watermark in it. Extraction of watermark image is done by applying inverse DWT, inverse DCT and SVD. The Peak Signal to Noise Ratio (PSNR) of the original EOG signal vs. watermarked signal and the correlation value between the original and extracted watermark image are calculated to prove the efficacy of the proposed method.

Stationary Wavelet Transformation Based Self-recovery of Blind-Watermark from Electrocardiogram Signal in Wireless Telecardiology

At present, considerable amount of work has been done in tele-monitoring that involves transmission of biomedical signals through wireless media. Exchange of bio-signals between hospitals requires efficient and reliable transmission. Watermarking is added “ownership” information in multimedia content to prove authenticity, verify signal integrity, and achieve control over the copy process. The ECG signal is a sensitive diagnostic tool that is used to detect various cardio-vascular diseases by measuring and recording the electrical activity of the heart in exquisite detail. This paper proposes a method of binary watermark embedding into the Electrocardiogram (ECG) signal and a self recovery based watermark extraction mechanism using Stationary Wavelet Transformation (SWT), Spread-Spectrum and quantization. In this approach, the generated watermarked signal having an acceptable level of imperceptibility and distortion is compared to the original ECG signal. Finally, a comparative study of detected P-QRS-T components is done to measure the diagnostic value change as an effect of watermarking. In this approach the generated watermarked ECG signal having an acceptable level of imperceptibility and distortion is compared to the Original ECG signal based on Peak Signal to Noise Ratio (PSNR) and correlation value.

Optical cup to disc ratio measurement for glaucoma diagnosis using harris corner

In medical study, retinal image processing plays a vital role in detecting the abnormalities of eye or ocular diseases like Glaucoma and diabetic retinopathy. Glaucoma is one of the two major causes of blindness worldwide, accounting for approximately 13% of visually impaired people. Glaucoma is physiologically described as the deterioration of optic nerve cells, and is characterized by alterations in the optic nerve head and visual field. The measurement of neuro-retinal optic cup-to-disc ratio (CDR) is an important index of Glaucoma, as the increased excavation of the optic cup occurs because of Glaucomatous neuropathy increasing the CDR. Currently, CDR evaluation is manually performed by ophthalmologists. Due to the interweavement of blood vessels with the surrounding tissues around the cup, automatic calculation of optic cup boundary thus being challenging. In this paper, an automatic method for CDR determination using Harris Corner is proposed.

Detection and measurement of bimalleolar fractures using Harris corner

Medical image processing covers a wide spectrum of activities growing vigorously in the last couple of decades. In this paper a method is proposed to detect ankle fractures with the help of wavelet analysis from the X-ray image of the fractured region. The wavelet analysis enables the availability of spectral information in low frequency region for short duration. One very common type of ankle fracture is bimalleolar fracture, in people belonging to the age group of 60 and above. By the proposed method, tracing the boundary of the displaced bone from the X-ray images is done by using Discrete Wavelet Transformation and gradient magnitude based segmentation followed by Canny edge detection. The measurement of displacement of the displaced bone is carried out with the help of Harris corner detection. The efficacy of the proposed method claims the distinct assessment for both lateral malleoli and medial malleoli.