Search

Your search keyword '"Harikrishna Kamatham"' showing total 6 results
Start Over Author "Harikrishna Kamatham"
6 results on '"Harikrishna Kamatham"'

1. An adaptive decision based interpolation scheme for the removal of high density salt and pepper noise in images

Author

Vasanth Kishorebabu, Ganesan Packyanathan, Harikrishna Kamatham, and Vishnu Shankar

Subjects
Salt and pepper noise, Interpolation technique, Inverse distance weighted interpolation, Edge preservation, Electronics, TK7800-8360
Abstract

Abstract An adaptive decision based inverse distance weighted interpolation (DBIDWI) algorithm for the elimination of high-density salt and pepper noise in images is proposed. The pixel is initially checked for salt and pepper noise. If classified as noisy pixel, replace it with an inverse distance weighted interpolation value. This interpolation estimates the values of corrupted pixels using the distance and values nearby non-noisy pixels in vicinity. Inverse distance weighted interpolation uses the contribution of non-noisy pixel to the interpolated value. The window size is varied adaptively depending upon the non-noisy content of the current processing window. The algorithm is tested on various images and found to exhibit good results both in terms of quantitative (PSNR, MSE, SSIM, Pratt’s FOM) and qualitative (visually) at high noise densities. The algorithm performs very well in restoring an image corrupted by high-density salt and pepper noise by preserving fine details of an image.

Published
2017
Full Text
View/download PDF

5. A Model-Based Approach for Extracting Emotional Status From Immobilized Beings Using EEG Signals

Author

Namana Murali Krishna, Harikrishna Kamatham, G. Raja Vikram, and J. Sirisha Devi

Abstract

Human-computer interaction is a potential area of interest since the birth of the computer era. The chapter highlights the usage of electroencephalogram (EEG wave) signals to initiate a conveying medium for immobilized persons, who are not able to express their feelings, by the use of human brain waves or signals. In order to recognize the human feelings or expressions with some emotion by an disable persons, a classifier based on a gamma distribution is utilized. The characteristic of the human brain waves are extracted with the usage of cepstral coefficients. The extracted characteristic is classified into various emotion states using generalized gamma distribution. In order to experiment the proposed model, six healthy persons or subjects are taken aged between from 20 and 28, and a 64 electrode channel EEG system is considered to gather the EEG brain signals under audio as well as visual stimuli. In this chapter, the authors focused the study on four basic human emotions: boredom, sad, happy, and neutral.

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results