Sri Krishna College of Engineering & Technology

About: Sri Krishna College of Engineering & Technology is a based out in . It is known for research contribution in the topics: Computer science & Wireless sensor network. The organization has 1915 authors who have published 1307 publications receiving 7585 citations.

A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises

Abstract: A new decision-based algorithm is proposed for restoration of images that are highly corrupted by impulse noise. The new algorithm shows significantly better image quality than a standard median filter (SMF), adaptive median filters (AMF), a threshold decomposition filter (TDF), cascade, and recursive nonlinear filters. The proposed method, unlike other nonlinear filters, removes only corrupted pixel by the median value or by its neighboring pixel value. As a result of this, the proposed method removes the noise effectively even at noise level as high as 90% and preserves the edges without any loss up to 80% of noise level. The proposed algorithm (PA) is tested on different images and is found to produce better results in terms of the qualitative and quantitative measures of the image

Prospective of the cosmeceuticals derived from marine organisms

Abstract: Cosmeceuticals, derived from the words ‘cosmetic and pharmaceutical’, have drug-like benefits and contain active ingredients such as vitamins, phytochemicals, enzymes, antioxidants, and essential oils. Cosmeceuticals have attracted increased attention because of their beneficial effects on human health. Bioactive substances derived from marine organisms have diverse functional roles as a secondary metabolite and these properties can be applied to the developments of novel pharmaceuticals and cosmeceuticals. Recently, extensive studies have been conducted on the general aspects of the chemical structures, physical and biochemical properties, and biotechnological applications of bioactive substances derived from marine organisms. In this review, we have discussed recent progresses in the biotechnological applications of bioactive substances from marine organisms as cosmeceuticals.

Optimised denoising scheme via opposition-based self-adaptive learning PSO algorithm for wavelet-based ECG signal noise reduction

Abstract: Electrocardiogram (ECG) signal is significant to diagnose cardiac arrhythmia among various biological signals. The accurate analysis of noisy electrocardiographic (ECG) signal is a very motivating challenge. According to this automated analysis, the noises present in electrocardiogram signal need to be removed for perfect diagnosis. Numerous investigators have been reported different techniques for denoising the electrocardiographic signal in recent years. In this paper, an efficient scheme for denoising electrocardiogram (ECG) signals is proposed based on a wavelet-based threshold mechanism. This scheme is based on an opposition-based self-adaptive learning particle swarm optimisation (OSLPSO) in dual tree complex wavelet packet scheme, in which the OSLPSO is utilised to for threshold optimisation. Different abnormal and normal electrocardiographic signals are tested to evaluate this approach from MIT/BIH arrhythmia database, by artificially adding white Gaussian noises with variation of 5 dB, 10 dB and 15 dB. Simulation results illustrate that the proposed system has good performance in various noise level and obtains better visual quality compared with other methods.

A New and Efficient Algorithm for the Removal of High Density Salt and Pepper Noise in Images and Videos

Abstract: A new and efficient algorithm for high-density salt and pepper noise removal in images and videos is proposed. The existing non-linear filter like Standard Median Filter (SMF), Adaptive Median Filter (AMF), Decision Based Algorithm (DBA) and Robust Estimation Algorithm (REA) shows better results at low and medium noise densities. At high noise densities, their performance is poor. A new algorithm to remove high-density salt and pepper noise using modified sheer sorting method is proposed. The new algorithm has lower computation time when compared to other standard algorithms. Results of the algorithm is compared with various existing algorithms and it is proved that the new method has better visual appearance and quantitative measures at higher noise densities as high as 90%.