A synergy of techniques on hybrid intelligence for real-life image analysis
Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding.
The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis.
Key features:
* Provides in-depth analysis of hybrid intelligent paradigms.
* Divided into self-contained chapters.
* Provides ample case studies, illustrations and photographs of real-life examples to illustrate findings and applications of different hybrid intelligent paradigms.
* Offers new solutions to recent problems in computer science, specifically in the application of hybrid intelligent techniques for image analysis and understanding, using well-known contemporary algorithms.
The book is essential reading for lecturers, researchers and graduate students in electrical engineering and computer science.
Autorentext
PROF. (DR.) SIDDHARTHA BHATTACHARYYA (SMIEEE, SMACM, LMCSI, LMOSI, LMISTE, MIAENG, MIRSS, MACSE, MIAASSE) obtained his Bachelors in Physics, Optics and Optoelectronics and Masters in Optics and Optoelectronics from the University of Calcutta, India, in 1995, 1998 and 2000 respectively. He completed a PhD in Computer Science and Engineering from Jadavpur University, India, in 2008. He is currently the Professor and Head of Information Technology at the RCC Institute of Information Technology, Kolkata, India. He is also the Dean (Research & Development) of the institute. He is a co-author of 3 books and co-editor of 5 books and more than 135 research publications.
DR. INDRAJIT PAN did his Bachelors in Computer Science Engineering in 2005 at The University of Burdwan, India, and completed his Masters in Information Technology at Bengal Engineering and Science University, Shibpur. He got a University Medal for his performance in his Masters. Later, he was awarded a PhD in Engineering from the Indian Institute of Engineering, Science and Technology (IIEST). He has more than 10 years' experience teaching in undergraduate and postgraduate engineering in IT and allied field. Currently, he is an Assistant Professor of Information Technology at the RCC Institute of Information Technology. His research interests include CAD, Computer Security, Soft Computing Applications and Cloud Computing.
DR. ANIRBAN MUKHERJEE did his Bachelors in Civil Engineering in 1994 at Jadavpur University, Kolkata. He completed his PhD on 'Automatic Diagram Drawing based on Natural Language Text Understanding' at the Indian Institute of Engineering, Science and Technology (IIEST), Shibpur, in 2014. He has more than 20 years' experience in teaching undergraduate and postgraduate engineering in IT and allied field. Currently, he is an Associate Professor and HOD of Engineering Science & Management at the RCC Institute of Information Technology. He has experience of working in computer aided design and engineering analysis and also of teaching on CAD courses. His research interests include Computer Graphics & CAD, Soft Computing Applications and
Assistive Technology. He has co-authored two UG engineering textbooks: a popular one on 'Computer Graphics and Multimedia' and another on 'Engineering Mechanics'. He has also co-authored more than 15 books on Computer Graphics/Multimedia for distance learning professional courses at different Universities in India.
PROF. (DR.) PARAMARTHA DUTTA has a B. Stat. (Hons.), M. Stat., M. Tech in Computer Science, and a PhD (Engineering) in Computer Science and Technology. With around 23 years of research and academic experience, Professor Dutta is currently serving as a Professor in the Department of Computer and System Sciences, Visva Bharati University. Professor Dutta is a senior Member of IEEE and ACM. He has executed almost 200 projects
funded by the Govt. of India. Professor Dutta has remained associated with various Universities and Institutes as
Visiting/Guest faculty. To date, Professor Dutta has more than 6 authored and 6 edited books in addition to around
180 papers, published in different International Journals and in International/National conference proceedings.
Inhalt
Editor Biographies xvii
List of Contributors xxi
Foreword xxvii
Preface xxxi
About the Companion website xxxv
1 Multilevel Image Segmentation UsingModified Genetic Algorithm (MfGA)-based Fuzzy C-Means 1
Sourav De, Sunanda Das, Siddhartha Bhattacharyya, and Paramartha Dutta
1.1 Introduction 1
1.2 Fuzzy C-Means Algorithm 5
1.3 Modified Genetic Algorithms 6
1.4 Quality Evaluation Metrics for Image Segmentation 8
1.4.1 Correlation Coefficient 8
1.4.2 Empirical Measure Q(I) 8
1.5 MfGA-Based FCM Algorithm 9
1.6 Experimental Results and Discussion 11
1.7 Conclusion 22
References 22
2 Character Recognition Using Entropy-Based Fuzzy C-Means Clustering 25
B. Kondalarao, S. Sahoo, and D.K. Pratihar
2.1 Introduction 25
2.2 Tools and Techniques Used 27
2.2.1 Fuzzy Clustering Algorithms 27
2.2.1.1 Fuzzy C-means Algorithm 28
2.2.1.2 Entropy-based Fuzzy Clustering 29
2.2.1.3 Entropy-based Fuzzy C-Means Algorithm 29
2.2.2 Sammon's Nonlinear Mapping 30
2.3 Methodology 31
2.3.1 Data Collection 31
2.3.2 Preprocessing 31
2.3.3 Feature Extraction 32
2.3.4 Classification and Recognition 34
2.4 Results and Discussion 34
2.5 Conclusion and Future Scope ofWork 38
References 39
Appendix 41
3 A Two-Stage Approach to Handwritten Indic Script Identification 47
Pawan Kumar Singh, Supratim Das, Ram Sarkar, andMita Nasipuri
3.1 Introduction 47
3.2 Review of RelatedWork 48
3.3 Properties of Scripts Used in the PresentWork 51
3.4 ProposedWork 52
3.4.1 DiscreteWavelet Transform 53
3.4.1.1 HaarWavelet Transform 55
3.4.2 Radon Transform (RT) 57
3.5 Experimental Results and Discussion 63
3.5.1 Evaluation of the Present Technique 65
3.5.1.1 Statistical Significance Tests 66
3.5.2 Statistical Performance Analysis of SVM Classifier 68
3.5.3 Comparison with Other RelatedWorks 71
3.5.4 Error Analysis 73
3.6 Conclusion 74
Acknowledgments 75
References 75
4 Feature Extraction and Segmentation Techniques in a Static Hand Gesture Recognition System 79
Subhamoy Chatterjee, Piyush Bhandari, and Mahesh Kumar Kolekar
4.1 Introduction 79
4.2 Segmentation Techniques 81
4.2.1 Otsu Method for Gesture Segmentation 81
4.2.2 Color SpaceBased Models for Hand Gesture Segmentation 82
4.2.2.1 RGB Color SpaceBased Segmentation 82
4.2.2.2 HSI Color SpaceBased Segmentation 83
4.2.2.3 YCbCr Color SpaceBased Segmentation 83
4.2.2.4 YIQ Color SpaceBased Segmentation 83
4.2.3 Robust Skin Color Region Detection Using K-Means Clustering and Mahalanobish Distance 84
4.2.3.1 Rotation Normalization 85
4.2.3.2 Illumination Normalization 85
4.2.3.3 Morphological Filtering 85
4.3 Feature Extraction Techniques 86
4.3.1 Theory of Moment Features 86
4.3.2 Contour-Based Features 88
4.4 State of the Art of Static Hand Gesture Recognition Techniques 89
4.4.1 Zoning Methods 90
4.4.2 F-Ratio-BasedWeighted Feature Extraction 90
4.4.3 Feature Fus…