Sensors and Image Processing (eBook, PDF)

Proceedings of CSI 2015
Redaktion: Urooj, Shabana; Virmani, Jitendra

• Format: PDF

Produktbeschreibung

The title 'Sensors and Image Processing' highlights the different applications in the field of Virtual Reality

It also delves into the matter as to how robotic can be applied to strengthen modelling

The title also showcases the various augments of latest mobile technologies, solid modelling, etc

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 275
• Erscheinungstermin: 3. Oktober 2017
• Englisch
• ISBN-13: 9789811066146
• Artikelnr.: 52938075

Autorenporträt

Dr. Shabana Urooj currently works at Gautam Buddha University, Greater Noida, India. She received her bachelor's in electrical engineering and M.Tech. in instrumentation & control from Aligarh Muslim University, Aligarh, India. She has completed her doctorate at Jamia Millia Islamia (A Central University), New Delhi, India. She has three years of industrial and 15 years of teaching experience. She has authored/co-authored more than 90 research papers. She has served as an editor, board member and reviewer for a number of leading journals. She is an active volunteer of IEEE and actively involved in various professional development ventures and bodies, such as the CSI and the ISTE. ;">Jitendra Virmani received his B.Tech. (Hons) in instrumentation engineering from Sant Longowal Institute of Engineering and Technology, Punjab in 1999 and his M.Tech. in electrical engineering with specialisation in measurement and instrumentation from the Indian Institute of Technology Roorkee, India in 2006, and his PhD on analysis and classification of B-Mode liver ultrasound images from the same institute in 2014. He held various academic posts before joining the Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, Punjab, India where he has been an assistant professor since July 2015. He is a life member of the Institute of Engineers (IEI), India. His research interests include application of machine learning and soft computing techniques for the analysis of medical images.

Inhaltsangabe

A Comparative Study of Various Color Texture Features for Skin Cancer Detection.- Pattern Classification and Retrieval of Content Based Images - A Step Towards Amelioration.- Novel Threshold Formulation for Energy Detection Method to Efficient Spectrum Sensing in Cognitive Radio.- Advanced technique to Crawl the images.- A Novel Web Page Change Detection Technique for Migrating Crawlers.- Developing Prototype for Prosopagnosia Using PCA.- Implementation of Smart Video Surveillance System Using Motion Detection Technique.- Intelligent Algorithm for Automatic Multistoried Parking System Using Image Processing, with Vehicle Tracking and Monitoring from Different Locations in the Building.- Computer Aided Detection of Breast Cancer Using Pseudo Zernike Moment as a Texture Descriptors.- Analysis of Leukoderma Images using Neuro-Fuzzy Hybrid Technique.- Texture and Clustering-Based Skin Disease Classification.- Melanoma Skin Cancer Detection Using Image Processing.- Performance Assessment for Clustering Techniques for Image Segmentation.- Automatic Seed Point Selection in B-Mode Breast Ultrasound Images.- EEA-LEACH - Trustworthy Enhanced Algorithm for Energy Optimization in Wireless Sensor Networks.- Secure Cluster Based Data Integrity Routing for Wireless Sensor Networks.- Objects Detection and Tracking Strategies.- Road Accident Informer System.- Hybrid Intelligent Algorithm for Energy Efficient Routing in WSN.- A Method for Secret Image Transmission to Preserve Privacy.- Text Retrieval from Scanned Forms Using Optical Character Recognition.- Combined Approach of Fuzzy Image Blocking Implementation for Medical Image Fusion.- A Systematic Review on Image Enhancement Techniques.- Virtual Field and Wave Laboratory Using Scilab and JAVA.- Classification and Comparative Study of IRS LISS-III Satellite Images Using RBFN and Decision Tree.- An Analytic Review on Image Enhancement Techniques Based on Soft Computing Approach.- An Auto-Threshold Control for Isolating False Shadowfrom High-Resolution Images.