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Advances in Soft Computing and Machine Learning in Image Processing

  • Book
  • © 2018

Overview

Editors:
  1. Aboul Ella Hassanien

    1. Faculty of Computers and Information, Information Technology Department, Cairo University, Giza, Egypt

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  2. Diego Alberto Oliva

    1. CUCEI, Departamento de Ciencias Computacionales, Universidad de Guadalajara, Guadalajara, Mexico

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  • Provides a collection of high-quality research work that addresses broad challenges in both theoretical and application aspects of soft computing and machine learning in image processing and computer vision
  • Presents original research that stimulates the continuing efforts on the application of computational intelligence (CI) approaches to solve image-processing problems and computer vision problems
  • Written by experts in the field
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 730)

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Table of contents (31 chapters)

  1. Front Matter

    Pages i-xii
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  2. Image Segmentation

    1. Front Matter

      Pages 1-1
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    2. Color Spaces Advantages and Disadvantages in Image Color Clustering Segmentation

      • Edgar Chavolla, Daniel Zaldivar, Erik Cuevas, Marco A. Perez
      Pages 3-22

    3. Multi-objective Whale Optimization Algorithm for Multilevel Thresholding Segmentation

      • Mohamed Abd El Aziz, Ahmed A. Ewees, Aboul Ella Hassanien, Mohammed Mudhsh, Shengwu Xiong
      Pages 23-39

    4. Evaluating Swarm Optimization Algorithms for Segmentation of Liver Images

      • Abdalla Mostafa, Essam H. Houssein, Mohamed Houseni, Aboul Ella Hassanien, Hesham Hefny
      Pages 41-62

    5. Thermal Image Segmentation Using Evolutionary Computation Techniques

      • Salvador Hinojosa, Gonzalo Pajares, Erik Cuevas, Noé Ortega-Sanchez
      Pages 63-88

    6. News Videos Segmentation Using Dominant Colors Representation

      • Ibrahim A. Zedan, Khaled M. Elsayed, Eid Emary
      Pages 89-109

  3. Applications of Image Processing in Medicine

    1. Front Matter

      Pages 111-111
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    2. Normalized Multiple Features Fusion Based on PCA and Multiple Classifiers Voting in CT Liver Tumor Recognition

      • Ahmed M. Anter, Aboul Ella Hassenian
      Pages 113-129

    3. Computer-Aided Acute Lymphoblastic Leukemia Diagnosis System Based on Image Analysis

      • Ahmed M. Abdeldaim, Ahmed T. Sahlol, Mohamed Elhoseny, Aboul Ella Hassanien
      Pages 131-147

    4. Telemammography: A Novel Approach for Early Detection of Breast Cancer Through Wavelets Based Image Processing and Machine Learning Techniques

      • Liyakathunisa Syed, Saima Jabeen, S. Manimala
      Pages 149-183

    5. Image Processing in Biomedical Science

      • Lakshay Bajaj, Kannu Gupta, Yasha Hasija
      Pages 185-211

    6. Automatic Detection and Quantification of Calcium Objects from Clinical Images for Risk Level Assessment of Coronary Disease

      • R. Priyatharshini, S. Chitrakala
      Pages 213-225

    7. Semi-automated Method for the Glaucoma Monitoring

      • Nesma Settouti, Mostafa El Habib Daho, Mohammed El Amine Bechar, Mohamed Amine Lazouni, Mohammed Amine Chikh
      Pages 227-246

  4. Security and Biometric Applications of Image Processing

    1. Front Matter

      Pages 247-247
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    2. Multimodal Biometric Personal Identification and Verification

      • Mohamed Elhoseny, Ahmed Elkhateb, Ahmed Sahlol, Aboul Ella Hassanien
      Pages 249-276

    3. Suspicious and Violent Activity Detection of Humans Using HOG Features and SVM Classifier in Surveillance Videos

      • Produte Kumar Roy, Hari Om
      Pages 277-294

    4. Hybrid Rough Neural Network Model for Signature Recognition

      • Mohamed Elhoseny, Amir Nabil, Aboul Ella Hassanien, Diego Oliva
      Pages 295-318

    5. A Novel Secure Personal Authentication System with Finger in Face Watermarking Mechanism

      • Chinta Someswara Rao, K. V. S. Murthy, R. Shiva Shankar, V. Mnssvkr Gupta
      Pages 319-353

    6. Activity Recognition Using Imagery for Smart Home Monitoring

      • Bradley Schneider, Tanvi Banerjee
      Pages 355-371
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Keywords

About this book

This book is a collection of the latest applications of methods from soft computing and machine learning in image processing. It explores different areas ranging from image segmentation to the object recognition using complex approaches, and includes the theory of the methodologies used to provide an overview of the application of these tools in image processing.

The material has been compiled from a scientific perspective, and the book is primarily intended for undergraduate and postgraduate science, engineering, and computational mathematics students.  It can also be used for courses on artificial intelligence, advanced image processing, and computational intelligence, and is a valuable resource for researchers in the evolutionary computation, artificial intelligence and image processing communities.

Reviews

“Every chapter is well written and comprehensive. New algorithms are presented with experimental results and performance comparisons. The reference materials used are clearly cited. Overall, this well-edited volume consists of rich, highly useful, and relevant material. It will be useful for research students working in soft computing, machine vision, and image processing fields.” (S. Ramakrishnan, Computing Reviews, July, 2018)​

Editors and Affiliations

  • Faculty of Computers and Information, Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  • CUCEI, Departamento de Ciencias Computacionales, Universidad de Guadalajara, Guadalajara, Mexico

    Diego Alberto Oliva

Bibliographic Information

  • Book Title: Advances in Soft Computing and Machine Learning in Image Processing

  • Editors: Aboul Ella Hassanien, Diego Alberto Oliva

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-319-63754-9

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2018

  • Hardcover ISBN: 978-3-319-63753-2Published: 25 October 2017

  • Softcover ISBN: 978-3-319-87627-6Published: 09 September 2018

  • eBook ISBN: 978-3-319-63754-9Published: 13 October 2017

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XII, 718

  • Number of Illustrations: 114 b/w illustrations, 195 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence, Signal, Image and Speech Processing

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