Pushpa Mamoria

Work place: Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Lucknow, India

E-mail: p.mat76@gmail.com

Website:

Research Interests: Image Processing, Network Security, Network Architecture, Image Manipulation, Image Compression, Neural Networks, Artificial Intelligence

Biography

Pushpa Mamoria received her BE degree in Computer Science and Engineering, from Shri G.S. Institute of Technology and Science, Indore (MP), INDIA and M. Tech. degree in Computer Science, from School of Computer Science, DAVV, Indore. She is currently pursuing her PhD degree from the Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Lucknow, India. Her major research interests include Digital Image Processing, Fuzzy Logic, Neural Network, Artificial Intelligence, cognitive science, wireless sensor networks.

Author Articles
An Analysis of Fuzzy and Spatial Methods for Edge Detection

By Pushpa Mamoria Deepa Raj

DOI: https://doi.org/10.5815/ijieeb.2016.06.08, Pub. Date: 8 Nov. 2016

An image segmentation is an area in which image is subdivided into sub-regions for extracting characteristics of images which will help to analysis in various applications. For getting accuracy sharp changes of intensity is an important issue which is known as edge detection. In this paper various spatial edge detection methods and fuzzy based edge detection method has described and spatial edge detection methods and fuzzy if-then-else are compared to know which method will be more suitable to find edges for the enhancement of images.

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Comparison of Mamdani Fuzzy Inference System for Multiple Membership Functions

By Pushpa Mamoria Deepa Raj

DOI: https://doi.org/10.5815/ijigsp.2016.09.04, Pub. Date: 8 Sep. 2016

Contrast enhancement is an emerging method for image enhancement of specific application to analyze the images clearer for interpretation and analysis in the spatial domain. The goal of Contrast enhancement is to serve an input image so that resultant image is more suited to the particular application. Images with good steps of grays between black and white are commonly the best images for the aim of human perception, a novel approach is proposed in this paper based on fuzzy logic. Mamdani fuzzy inference system models are developed to enhance the contrast of images based on different membership functions (MFs). 

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