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Retinal fundus photographs has always remained the gold standard for evaluating the changes in retina. Here, a novel method for automatic glaucoma detection from digital retinal fundus images is proposed. The methodology makes use of optic disc and cup segmentation. Optic disc is segmented using morphological operations and hybrid level-set methodology. Optic cup is segmented by first detecting blood...
This study presents an innovative approach to detect drowsiness by using photoplethysmography signals which is easily acquirable with non-invasive techniques. Drowsiness detection based on biological signals is being employed in precautionary personal safety. Autonomous Nervous System (ANS) activity can be measured non-invasively from the Pulse Rate Variability (PRV) signal obtained from photoplethysmography...
In this paper a new technique to enhance the medical images without distorting the local information is proposed. Proposed method is capable of reducing the over-enhancement problem. The method first cluster the gray levels based on certain criteria and then the new transformation function is applied to each cluster. Proposed method uses Averaging method to transform the gray levels in each cluster...
In this paper, a non linear adaptive Gaussian de-noising method for diffusion tensor imaging (DTI) is proposed. DTI image are of poor SNR and low resolution images. In order to improve DTI, the proposed method is applied to the diffusion weighted images (DWI) from which DTI is computed. The anisotropic flow principle is used in non linear adaptive Gaussian denoising method and smoothing will vary...
In this paper, a new denoising and contrast enhancement method for DTI is proposed. Noise removal is given priority in existing denoising methods. In order to increase the visibility of structural details, contrast enhancement methods has to be used. In proposed method, a non-linear adaptive Gaussian denoising filter removes noises from the DTI. To increase the visibility of filtered micro structural...
This paper presents the application of two different image enhancement techniques to medical images and the comparison of these techniques with traditional Histogram Equalization (HE) method. The proposed method uses Weighted Histogram Equalization (WHE) and transform domain approach to enhance medical images. Simulation results shows that Perona-Malik filter (PM filter) can be used to remove the...
The frequency modulated continuous wave (FMCW) radar principle has been used in altimeter to measure altitude above the surface of the Earth. Traditionally it has been used in short range application due to its unambiguous range. The enhanced range resolution is a factor for FMCW radars compared with other types of radars. There are theoretical restrictions in the range resolution. This paper deals...
Compressed Sensing is an emerging methodology to reconstruct signals with smaller number of projections. Nyquist rate yields too many samples, which is high for broadband signals that are used in many applications. The proposed method unveils the application of compressed sensing in the channel estimation of Orthogonal Frequency Division Multiplexing (OFDM). l1-regularized Least square problem solver...
A medical image denoising algorithm using contour let transform is proposed and the performance of the proposed method is analysed with the existing methods. Noise in magnetic resonance imaging has a Rician distribution and unlike AWGN noise, Rician noise is signal dependent. Separating signal from Rician noise is a tedious task. The proposed approaches were compared with other transform methods such...
Implementation of radix-2 and split-radix fast Fourier transform (FFT) algorithm using analog CMOS current mirrors with a reduction in the count of transistors and propagation delay is presented. The proposed method reduces the number of transistors required to implement analog FFTs and the percentage reduction increases considerably for higher point FFTs. It is shown that the number of transistors...
Detection and localization of texts from natural scene images is important and can provide a much truer form of content-based image analysis if it can be extracted and harnessed efficiently. This problem becomes challenging because of complex background, variations of text font, size and line orientation, non-uniform illumination. A new unsupervised text detection algorithm is proposed in this paper...
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