Shruti Mathur

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Detection of Brain Tumor in MRI Image through Fuzzy-Based Approach

High-Resolution Neuroimaging - Basic Physical Principles and Clinical Applications, 2018

The process of accurate detection of edges of MRI images of a brain is always a challenging but i... more The process of accurate detection of edges of MRI images of a brain is always a challenging but interesting problem. Accurate detection is very important and critical for the generation of correct diagnosis. The major problem that comes across while analyzing MRI images of a brain is inaccurate data. The process of segmentation of brain MRI image involves the problem of searching anatomical regions of interest, which can help radiologists to extract shapes, appearance, and other structural features for diagnosis of diseases or treatment evaluation. The brain image segmentation is composed of many stages. During the last few years, preprocessing algorithms, techniques, and operators have emerged as a powerful tool for efficient extraction of regions of interest, performing basic algebraic operations on images, enhancing specific image features, and reducing data on both resolution and brightness. Edge detection is one of the techniques of image segmentation. Here from image segmentation, tumor is located. Finally, we try to retrieve tumor from MRI image of a brain in the form of edge more accurately and efficiently, by enhancing the performance of diffe rent kinds of edge detectors using fuzzy approach.

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A Brief Survey of Deep Learning Techniques for Person Re-identification

2020 3rd International Conference on Emerging Technologies in Computer Engineering: Machine Learning and Internet of Things (ICETCE), 2020

Over the past decade’s person re-identification is being a hot research area and an active partic... more Over the past decade’s person re-identification is being a hot research area and an active participant in the automated video surveillance. Besides monitoring of person of interest and human-machine interaction, person re-identification is also used in broadcast media and in forensic examination. Images and videos captured from different cameras gets suffers from low quality and resolution issues which generates difficulty in extraction of useful information. Deep learning plays a vital role in person re-identification in retrieval and determining similarity among the features from data. With the advancement in the deep learning techniques, favorable performances are obtained while handling challenges obtained from diverse viewpoints, dazedness, resolutions in image, settings of camera, blocking of an object of interest and irregular background across camera views. This paper presentes the current challenges that are overcome by the usage of the deep learning architectures.

A Novel Approach to Improve Sobel Edge Detector

Procedia Computer Science, 2016

An improved edge detection algorithm based on k-means clustering approach. Being a fundamental to... more An improved edge detection algorithm based on k-means clustering approach. Being a fundamental tool in image processing, edge detection aims to identify the points in an image at which image brightness changes sharply or regularly. In Medical Science, edge detection is very useful, such as in segmentation of MRI image. Magnetic resonance imaging (MRI) produces a detailed image of any human body part, by using the natural magnetic properties of the body tissues. Since body tissues contain hydrogen atoms, which made to emit radio signals. These radio signals are then detected by a scanner. Magnetic Resonance imaging is a medical test used to diagnose tumors of the brain on the basis of high quality images produced by it. In this paper edge detection is made to determine the location of a tumor. The edge detection technique presented in this paper uses k-means clustering approach to generate the initial groups. These groups are then input to the mamdani fuzzy inference system, which generates different threshold parameters. When these parameters are fed into the classical sobel edge detector, it is found that images obtained are more enhanced and provide exact location of a tumor in a brain.

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An Analysis on Color Preservation Using Non-Shannon Entropy Measures for Gray and Color Images

2014 Fourth International Conference on Advances in Computing and Communications, 2014

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Shruti Mathur

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