Biologically Rationalized Computing Techniques For Image Processing Applications

1. Front Matter

   Pages i-vi

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2. Artificial Bee Colony Algorithm for Classification of Semi-urban LU/LC Features Using High-Resolution Satellite Data

   • J. Jayanth, T. Ashok Kumar, Shivaprakash Koliwad, V.S. Shalini

   Pages 1-20

3. Saliency-Based Image Compression Using Walsh–Hadamard Transform (WHT)

   • A. Diana Andrushia, R. Thangarjan

   Pages 21-42

4. Object Trajectory Prediction with Scarce Environment Information

   • Jin Sung Park, Daniela López De Luise, Jude Hemanth

   Pages 43-55

5. A Twofold Subspace Learning-Based Feature Fusion Strategy for Classification of EMG and EMG Spectrogram Images

   • Anil Hazarika, Manbendra Bhuyan

   Pages 57-84

6. Automatic Detection of Brain Strokes in CT Images Using Soft Computing Techniques

   • B. S. Maya, T. Asha

   Pages 85-109

7. Survey on the Classification of Intelligence-Based Biometric Techniques

   • K. Martin Sagayam, J. Felix Jacob Edwin, J. Sujith Christopher, Gowru Vamsidhar Reddy, Robert Bestak, Lim Chot Hun

   Pages 111-132

8. Spatial and Spectral Quality Assessment of Fused Hyperspectral and Multispectral Data

   • Somdatta Chakravortty, Anil Bhondekar

   Pages 133-158

9. Deep Learning Techniques for Breast Cancer Detection Using Medical Image Analysis

   • D. Selvathi, A. Aarthy Poornila

   Pages 159-186

10. A Tour Toward the Development of Various Techniques for Paralysis Detection Using Image Processing

    • Banita Banita, Poonam Tanwar

    Pages 187-214

11. Chlorella Algae Image Analysis Using Artificial Neural Network and Deep Learning

    • S. Lakshmi, R. Sivakumar

    Pages 215-248

12. Review on Image Enhancement Techniques Using Biologically Inspired Artificial Bee Colony Algorithms and Its Variants

    • Rehan Ahmad, Nitin S. Choubey

    Pages 249-271

13. Certain Applications and Case Studies of Evolutionary Computing Techniques for Image Processing

    • A. Vasuki

    Pages 273-296

14. Histopathological Image Analysis for the Grade Identification of Tumor

    • M. Monica Subashini

    Pages 297-316

15. Super-Resolution via Particle Swarm Optimization Variants

    • Maria Aparecida de Jesus, Vania V. Estrela, Osamu Saotome, Dalmo Stutz

    Pages 317-337

This book introduces readers to innovative bio-inspired computing techniques for image processing applications. It demonstrates how a significant drawback of image processing – not providing the simultaneous benefits of high accuracy and less complexity – can be overcome, proposing bio-inspired methodologies to help do so. 


Besides computing techniques, the book also sheds light on the various application areas related to image processing, and weighs the pros and cons of specific methodologies. Even though several such methodologies are available, most of them do not provide the simultaneous benefits of high accuracy and less complexity, which explains their low usage in connection with practical imaging applications, such as the medical scenario. Lastly, the book illustrates the methodologies in detail, making it suitable for newcomers to the field and advanced researchers alike.

• Bio-inspired algorithms
• Image processing
• Computational Intelligence
• Soft Computing
• Computer vision

• Karunya University, Coimbatore, India

  Jude Hemanth

• Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

  Valentina Emilia Balas

D. Jude Hemanth received his B.E degree in ECE from Bharathiar University in 2002, M.E degree in communication systems from Anna University in 2006 and Ph.D. from Karunya University in 2013. His research areas include Computational Intelligence and Image processing. He has authored more than 100 research papers in well-respected international journals such as Neurocomputing, Neural Computing and Applications, Neural Network World, etc. as well as book chapters published by well known publishers. He is very active in his field, holding membership of professional organisations and serving on committees and boards. Currently, he is working as Associate Professor in the Department of ECE, Karunya University, Coimbatore, India.

Valentina E. Balas is currently Full Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu” University of Arad, Romania. She holds a Ph.D. in Applied Electronics and Telecommunication

s from Polytechnic University of Timisoara. Dr. Balas is author of more than 250 research papers in refereed journals and International Conferences. Her research interests are in Intelligent Systems, Fuzzy Control, Soft Computing, Smart Sensors, Information Fusion, Modeling and Simulation. She is the Editor-in Chief to International Journal of Advanced Intelligence Paradigms (IJAIP) and to International Journal of Computational Systems Engineering (IJCSysE), Editorial Board member of several national and international journals and is evaluator expert for national and international projects. Dr. Balas is the director of Intelligent Systems Research Centre in Aurel Vlaicu University of Arad. She served as General Chair of the International Workshop Soft Computing and Applications (SOFA) in seven editions 2005-2016 held in Romania and Hungary. Dr. Balas participated in many international conferences as Organizer, Honorary Chair, Session Chair and member in Steering, Advisory or International Program Committees. She is a member of EUSFLAT, SIAM and a Senior Member IEEE, member in TC – Fuzzy Systems (IEEE CIS), member in TC - Emergent Technologies (IEEE CIS), member in TC – Soft Computing (IEEE SMCS). Dr. Balas was Vice-president (Awards) of IFSA International Fuzzy Systems Association Council (2013-2015) and is a Joint Secretary of the Governing Council of Forum for Interdisciplinary Mathematics (FIM), - A Multidisciplinary Academic Body, India.

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