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Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision

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Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision Edited by Karm Veer Arya, PhD Ciro Rodriguez Rodriguez, PhD Saurabh Singh, PhD Abhishek Singhal, PhD AAP Series on Digital Signal Processing, Computer Vision and Image Processing

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First edition published 2024 Apple Academic Press Inc. CRC Press 1265 Goldenrod Circle, NE, 2385 NW Executive Center Drive, Palm Bay, FL 32905 USA Suite 320, Boca Raton FL 33431 760 Laurentian Drive, Unit 19, 4 Park Square, Milton Park, Burlington, ON L7N 0A4, CANADA Abingdon, Oxon, OX14 4RN UK © 2024 by Apple Academic Press, Inc. Apple Academic Press exclusively co-publishes with CRC Press, an imprint of Taylor & Francis Group, LLC Reasonable efforts have been made to publish reliable data and information, but the authors, editors, and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors are solely responsible for all the chapter content, figures, tables, data etc. provided by them. The authors, editors, and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged, please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, access www.copyright.com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. For works that are not available on CCC please contact mpkbookspermissions@tandf.co.uk Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe. Library and Archives Canada Cataloguing in Publication Title: Artificial intelligence and machine learning techniques in image processing and computer vision / edited by Karm Veer Arya, PhD, Ciro Rodriguez Rodriguez, PhD, Saurabh Singh, PhD, Abhishek Singhal, PhD. Names: Arya, Karm Veer, editor. | Rodriguez, Ciro, editor. | Singh, Saurabh (Head of Department in the Department of Computer Science and Engineering), editor. | Singhal, Abhishek, editor. Description: First edition. | Series statement: AAP series on digital signal processing, computer vision and image processing | Includes bibliographical references and index. Identifiers: Canadiana (print) 2023057923X | Canadiana (ebook) 20230579248 | ISBN 9781774914694 (hardcover) | ISBN 9781774914687 (softcover) | ISBN 9781003425700 (ebook) Subjects: LCSH: Computer vision. | LCSH: Image processing. | LCSH: Artificial intelligence. | LCSH: Machine learning. | LCSH: Algorithms. Classification: LCC TA1634 .A78 2024 | DDC 006.3/7—dc23 Library of Congress Cataloging-in-Publication Data ISBN: 978-1-77491-469-4 (hbk) ISBN: 978-1-77491-468-7 (pbk) ISBN: 978-1-00342-570-0 (ebk) CIP data on file with US Library of C ongress

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AAP SERIES ON DIGITAL SIGNAL PROCESSING, COMPUTER VISION AND IMAGE PROCESSING BOOK SERIES EDITORS: Dr. Manoj Gupta, PhD Associate Professor, Department of Electronics and Communication Engineering, JECRC University, Jaipur (Rajasthan), India Email: manojgupta35@yahoo.co.in Dr. Pradeep Kumar, PhD Discipline of Electrical, Electronic and Computer Engineering, Howard College Campus, University of KwaZulu-Natal, Durban-4041, South Africa Email: pkumar_123@yahoo.com, kumarp@ukzn.ac.za Brief description of the Book Series: Digital signal processing, computer vision and image processing as a whole is considered to be one of the most rapidly evolving areas of research and technology today with growing applications in almost all disciplines of engineering. Medical imaging, computer vision, healthcare, medical applications, remote sensing, agriculture, robotics, communication systems and space exploration are some of the applications of digital signal processing, computer vision and image processing, to name a few. The present day curriculum covers many aspects of digital signal processing, computer vision and image processing, addressing the theoretical aspects in particular. This book series is intended to supplement the theoretical knowledge with special emphasis on the practical side. The series content has been specifically chosen to give a thorough understanding of the fundamental aspects to advanced applications of digital signal processing, computer vision and image processing.

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vi AAP Series on Digital Signal Processing, Computer Vision and Image Processing The series is open to monograph. handbooks, authored books, edited volumes, and conference proceedings. This series aim to embrace all aspects, sub fields and new challenges in the followings research domains (related topics) but are not limited to: • Image and Video Processing: Image filtering, restoration and enhancement, image segmentation, video segmentation and tracking, morphological processing, feature extraction and analysis, interpolation and super-resolution, motion detection and estima- tion, computer vision, pattern recognition, content-based image retrieval, image/signal computations and services, features and models for image/signals, machine learning based image and signal processing, data mining techniques, imaging algebra, mathematical morphology, probabilistic, statistical, optimization, approximation theory, models in imaging science, video signal processing, visu- alization, watermarking, video surveillance, video compression and streaming, video analysis and event recognition, biometrics, medical image analysis, artificial intelligence and related areas. • Signal Processing: Filters theory, spectral analysis, time-frequency and time-scale representation, EEG/ECG signals, FIR/IIR and adaptive filters, statistical signal processing, filtering, detection and estimation, nonlinear signal processing, radar, antennas, telecommunications systems, acoustics. Signal processing theory and methods, high signal processing: integrating 5G and IoT with satellite networks, hands-free speech communication and micro- phone arrays, wearable sensor signal processing, architecture and frameworks, audio/speech processing and coding, watermarking, data mining techniques, statistical and optical signal processing, communication signal processing, DSP system and embedded systems, multimedia processing, artificial intelligence , IoT, cyber physical systems and related areas. • Computer Vision: Algorithms, feature extraction and pattern recognition, ML and deep learning in vision, CBIR, object and face recognition, AR/VR, object detection and localization, 3D object extraction, tracking and visual navigation, cognitive and biological inspired vision, artificial intelligence, machine learning , ubiquitous computing and related areas.

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AAP Series on Digital Signal Processing, Computer Vision and Image Processing vii • Applications Areas: Biometric, bioinformatics and biomedical imaging, medial images and applications, healthcare applications, agriculture applications, augmented and mixed reality, mental health and cognitive stimulations, security and video-surveillance, quality control and inspection, archaeology, remote sensing, embedded systems and applications, automated vehicles, speech and music processing, robotics, rehabilitation, occupational therapy and tele- medicine, artificial intelligence and machine learning/deep learning based applications, cyber physical systems, Internet of Things (IoT), Industry 4.0, Medicine 5.0 and other related applications. BOOKS IN THE SERIES: Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision Editors: Karm Veer Arya, PhD, Ciro Rodriguez Rodrigues, PhD, Saurabh Singh, PhD, and Abhishek Singhal, PhD Computational Imaging and Analytics in Biomedical Engineering: Algorithms and Applications Editors: T. R. Ganesh Babu, PhD, U. Saravanakumar, PhD, and Balachandra Pattanaik, PhD

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ABOUT THE EDITORS Karm Veer Arya, PhD Faculty, Department of Information and Communication Technology; Coordinator of Multimedia and Information Security Research Group at ABV-IIITM, Gwalior, India Karm Veer Arya, PhD, is associated with the Department of Information and Communication Technology and Coordinator of Multimedia and Information Security Research Group at ABV-IIITM, Gwalior. He has more than 29 years of teaching and research experience. His research interests include image processing, biometrics, and artificial intelligence. Prof. Arya has published more than 150 research papers in various internationally reputed journals and conferences. He has supervised 11 PhD scholars and 92 PG students. Prof. Ayra is the recipient of Inspirational Scientist Award in the years 2020–2021. He has won Life Time Golden Achievement Award by Bharat Rattan Publishing House in year 2020. Ciro Rodriguez Rodriguez, PhD Ciro Rodriguez Rodriguez, PhD, is associated with the department of Soft- ware Engineering at National University Mayor de San Marcos and with the department of Informatics Engineering at National University Federico Villarreal. He has completed his PhD in Engineering and has advanced studies at the Institute of Theoretical Physics ICTP of Italy, in the United States Particle Accelerator School USPAS, and Information Technology Development Policy Studies Korea Telecom KT in South Korea. His research interests include artificial intelligence, health-social welfare, and environment. He has published over 80 research articles in reputed journals indexed in Scopus, WoS, IEEE, and filed two patents in engineering fields.

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x About the Editors Saurabh Singh, PhD Professor, School of Computing Science and Engineering at Galgotias University, Greater Noida, India. Saurabh Singh, PhD, is working as Professor in the School of Computing Science and Engineering, Galgotias University, Greater Noida India. Dr. Singh has more than 21 years of experience in teaching and research. He has received his PhD degree from Birla Institute of Technology, Ranchi. He has published over 40 research articles in various internationally reputed journals and conferences, written book chapters, and filed nine patents in various fields of engineering. Abhishek Singhal, PhD Associate Professor, Department of Computer Science and Engineering at Amity University, Noida, India Abhishek Singhal, PhD, is working as an Associate Professor in the Department of Computer Science and Engineering at Amity University, Noida. He has received his PhD from Amity University, Noida, in the year 2018. He has more than 22 years of experience. He has published over 50 Scopus-indexed research articles in various internationally reputed journals and conferences.

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CONTENTS Contributors ....................................................................................................... xiii Abbreviations .................................................................................................... xvii Preface ............................................................................................................... xxi PART I: Health Care Systems ............................................................................ 1 1. Machine Learning Model-Based Detection of Sperm Head Abnormalities from Stained Microscopic Images .................................... 3 Sakthi Jaya Sundar Rajasekar and Varalakshmi Perumal 2. Smart Healthcare System for Reliable Diagnosis of Polycystic Ovary Syndrome ..................................................................... 19 Ishika Dhall, Shubham Vashisth, and Garima Aggarwal 3. Classification of Breast Histopathological Images using Semi-Supervised Generative Adversarial Networks .............................. 37 Karthiga R, Usha G, and Narasimhan 4. A Systematic Review for the Classification and Segmentation of Diabetic Retinopathy Lesion from Fundus ............................................. 55 Alaguselvi R and Kalpana Murugan 5. Critical Analysis of Various Supervised Machine Learning Algorithms for Detecting Diabetic Retinopathy in Images ................... 75 Neetu Faujdar, Reeya Agrawal, and Ankush Agarwal PART II: Image and Video Processing ............................................................ 95 6. Artificial Bee Colony Optimization Technique-Based Video Copyright Protection in DWT-PCA Domain .......................................... 97 Ponnisathya S., Ramakrishnan S., and Sathiyamurthi P. 7. Gray Tone Spatial Dependence Matrix: Texture Feature for Image Classification .................................................................................111 Amit Verma

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8. Image Colorization and Restoration Using Deep Learning ................ 131 Aryan Raj Tiwary, Aditya Kr. Gupta, Preetish Niket, Tapas Khanijo, and Jyoti Gupta 9. Determining Image Scale in Real-World Units Using Natural Objects Present in Image ......................................................... 145 Saurabh Singh and Rhea S. Shrivastava 10. Image Segmentation Using Metaheuristic ............................................ 169 Abhishek Singhal and Sakshi Bisht PART III: Advanced Machine Learning ....................................................... 191 11. A Computer Vision Use Case: Detecting the Changes in Amazon Rainforest Over Time .............................................................. 193 Dwijendra Nath Dwiivedi and Ganesh Patil 12. Using CNN and Image Processing Approaches in the Preservation of Sea Turtles..................................................................... 207 Mireya Saraí García Vázquez and Alejandro Álvaro Ramírez Acosta 13. Deep Learning-Based Semantic Segmentation Techniques and Their Applications in Remote Sensing .................................................. 229 Preetpal Kaur Buttar and Manoj Kumar Sachan 14. Deep Convolutional Neural Network-Based Single Image Superresolution ....................................................................................... 259 Wazir Muhammad and Manoj Gupta 15 A Review of Machine Learning Techniques for Vision-Established Human Action Recognition ................................... 285 J. Palanimeera and K. Ponmozhi Index .................................................................................................................. 309 xii Contents

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CONTRIBUTORS Alejandro Álvaro Ramírez Acosta MIRAL R&D&I, San Diego, CA, USA Ankush Agarwal Department of Computer Engineering and Applications, GLA University, Mathura, India Reeya Agrawal Department of Computer Engineering and Applications, GLA University, Mathura, India Garima Aggarwal Department of Computer Science and Engineering, Amity University, Noida, India Sakshi Bisht Amity School of Engineering and Technology, Amity University, India Preetpal Kaur Buttar Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Punjab, India Ishika Dhall Department of Computer Science and Engineering, Amity University, Noida, India Dwijendra Nath Dwiivedi Krakow university of Economics, Kraków, Poland Neetu Faujdar Department of Computer Engineering and Applications, GLA University, Mathura, India Usha G. Department of ECE, Srinivasa Ramanujan Centre, SASTRA Deemed to be University, Kumbakonam, India Aditya Kr. Gupta Department of Electronics and Communication Engineering, Bharati Vidyapeeth College of Engineering, New Delhi, India Jyoti Gupta Department of Electronics and Communication Engineering, Bharati Vidyapeeth College of Engineering, New Delhi, India Manoj Gupta Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand Tapas Khanijo Department of Electronics and Communication Engineering, Bharati Vidyapeeth College of Engineering, New Delhi, India

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xiv Contributors Wazir Muhammad Department of Electrical Engineering, BUET, Khuzdar, Pakistan Kalpana Murugan Department of Electronics and Communication Engineering, Kalasalingam Academy of Research and Education, Virudhunagar, Tamil Nadu, India Narasimhan Department of ECE, School of EEE, SASTRA Deemed to be University, Thanjavur, India Preetish Niket Department of Electronics and Communication Engineering, Bharati Vidyapeeth College of Engineering, New Delhi, India Sathiyamurthi P. Department of Information Technology, Dr. Mahalingam College of Engineering & Technology, Pollachi, Tamil Nadu, India J. Palanimeera Department of Computer Applications, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, India Ganesh Patil Indian Institute of Management, Lucknow, India Varalakshmi Perumal Madras Institute of Technology, Anna University, Chennai, India K. Ponmozhi Department of Computer Applications, Kalasalingam Academy of Research and Education, Krishnankoil, Tamil Nadu, India Alaguselvi R. Department of Electronics and Communication Engineering, Kalasalingam Academy of Research and Education, Virudhunagar, Tamil Nadu, India Karthiga R. Department of ECE, School of EEE, SASTRA Deemed to be University, Thanjavur, India Sakthi Jaya Sundar Rajasekar Melmaruvathur Adhiparasakthi Institute of Medical Sciences and Research, Melmaruvathur, India Ponnisathya S. Department of Information Technology, Dr. Mahalingam College of Engineering & Technology, Pollachi, Tamil Nadu, India Ramakrishnan S. Department of Information Technology, Dr. Mahalingam College of Engineering & Technology, Pollachi, Tamil Nadu, India Manoj Kumar Sachan Department of Computer Science and Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Punjab, India Rhea S. Shrivastava Amity School of Engineering and Technology, Amity University, India

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Contributors xv Saurabh Singh Professor, School of Computing Science and Engineering at Galgotias University, Greater Noida, India Abhishek Singhal Amity School of Engineering and Technology, Amity University, India Aryan Raj Tiwary Department of Electronics and Communication Engineering, Bharati Vidyapeeth College of Engineering, New Delhi, India Shubham Vashisth Department of Computer Science and Engineering, Amity University, Noida, India Mireya Saraí García Vázquez Instituto Politécnico Nacional-CITEDI, Tijuana, BC, Mexico Amit Verma School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

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ABBREVIATIONS A adenosis ABC artificial bee colony ADFV absolute difference of frame variance AI artificial intelligence AMD age-related macular degeneration ART artificial reproductive techniques ASPP atrous spatial pyramid pooling AUC area under the curve BGR blue-green-red CAD computer-aided diagnosis CASA computer-aided sperm analysis CNF context-wise network fusion CNN convolutional neural networks CRFs conditional random fields CRP C-reactive protein CXR chest X-ray DC ductal carcinoma DC-GAN deep convolutional generative adversarial networks DCNN deep convolutional neural network DR diabetic retinopathy EX exudates FA fibroadenoma FCL fully connected layer FCNs fully convolutional networks FN false negatives FODPSO fractional order Darwinian particle swarm optimization FoV field-of-view FP false positives GA genetic algorithm GANs generative adversarial networks GLCM grey level co-occurrence matrix GPU graphics processing unit HAR human activity recognition

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xviii Abbreviations H&E hematoxylin and eosin HBMO honey-bee mating optimization HEMs hemorrhages HOG histogram of oriented gradients HR high-resolution HSN hourglass-shaped network HuSHeM human sperm head morphology dataset iDT improved density trajectory ILSVRC ImageNet Large Scale Visual Recognition Challenge IR infrared IS image segmentation IVF in vitro fertilization JPU Joint Pyramid Upsampling LBD lung boundary detection LBP local binary pattern LC lobular carcinoma LCF local convergence filters LR low-resolution LSTM long short-term memory LTD lung tumor detection MA microaneurysms MAP maximum a posteriori MC mucinous carcinoma MCIS multi-resolution color image segmentation MCNN multiscale CNN MIR mid-IR MLP multilayer perceptron MRF Markov random fields MRIs magnetic resonance imaging MSE means squared error NIR near-IR NPA natural protected areas OSA obstructive sleep apnea PC papillary carcinoma PCOS polycystic ovary syndrome PDE partial differential equations PNN probabilistic neural network PSNR peak signal-to-noise ratios

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Abbreviations xix PSO particle swarm optimization PT phyllodes tumor ReLU rectified linear unit RMSE root-mean-square error ROC receiver operating characteristics SA simulated annealing SIFT scale invariant feature transform SLAM simultaneous localization and mapping SP spatial pyramids SR super-resolution SSF scale-space filter SSGAN semi-supervised GAN SSIM structural similarity index SURF speeded up robust features SVM support vector machine TA tubular adenoma TN true negatives TP true positives VDSR very deep super-resolution VHR very high resolution VLAD vector of linearly aggregated descriptors WHO World Health Organization