Image Analysis and Recognition

Image Analysis and Recognition
Author: Mohamed Kamel
Publisher: Springer
Total Pages: 828
Release: 2013-06-05
Genre: Computers
ISBN: 3642390943

This book constitutes the thoroughly refereed proceedings of the 10th International Conference on Image Analysis and Recognition, ICIAR 2013, held in Póvoa do Varzim, Portugal, in June 2013, The 92 revised full papers presented were carefully reviewed and selected from 177 submissions. The papers are organized in topical sections on biometrics: behavioral; biometrics: physiological; classification and regression; object recognition; image processing and analysis: representations and models, compression, enhancement , feature detection and segmentation; 3D image analysis; tracking; medical imaging: image segmentation, image registration, image analysis, coronary image analysis, retinal image analysis, computer aided diagnosis, brain image analysis; cell image analysis; RGB-D camera applications; methods of moments; applications.

Image Analysis and Recognition

Image Analysis and Recognition
Author: Aurélio Campilho
Publisher: Springer Science & Business Media
Total Pages: 465
Release: 2010-06-09
Genre: Computers
ISBN: 3642137741

This book constitutes the thoroughly refereed proceedings of the 7th International Conference, ICIAR 2010, held in Póvoa de Varzin, Portugal in June 2010. The 88 revised full papers were selected from 164 submissions. The papers are organized in topical sections on Image Morphology, Enhancement and Restoration, Image Segmentation, Featue Extraction and Pattern Recognition, Computer Vision, Shape, Texture and Motion Analysis, Coding, Indexing, and Retrieval, Face Detection and Recognition, Biomedical Image Analysis, Biometrics and Applications

Pattern Recognition and Image Analysis

Pattern Recognition and Image Analysis
Author: Earl Gose
Publisher: Prentice Hall
Total Pages: 504
Release: 1996
Genre: Computers
ISBN:

Over the past 20 to 25 years, pattern recognition has become an important part of image processing applications where the input data is an image. This book is a complete introduction to pattern recognition and its increasing role in image processing. It covers the traditional issues of pattern recognition and also introduces two of the fastest growing areas: Image Processing and Artificial Neural Networks. Examples and digital images illustrate the techniques, while an appendix describes pattern recognition using the SAS statistical software system.

Machine Learning in Image Analysis and Pattern Recognition

Machine Learning in Image Analysis and Pattern Recognition
Author: Munish Kumar
Publisher: MDPI
Total Pages: 112
Release: 2021-09-08
Genre: Technology & Engineering
ISBN: 3036517146

This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.

Handbook Of Character Recognition And Document Image Analysis

Handbook Of Character Recognition And Document Image Analysis
Author: Horst Bunke
Publisher: World Scientific
Total Pages: 851
Release: 1997-05-02
Genre: Computers
ISBN: 9814500380

Optical character recognition and document image analysis have become very important areas with a fast growing number of researchers in the field. This comprehensive handbook with contributions by eminent experts, presents both the theoretical and practical aspects at an introductory level wherever possible.

Document Image Analysis

Document Image Analysis
Author: K.C. Santosh
Publisher: Springer
Total Pages: 184
Release: 2018-09-18
Genre: Computers
ISBN: 9811323399

The book focuses on one of the key issues in document image processing – graphical symbol recognition, which is a sub-field of the larger research domain of pattern recognition. It covers several approaches: statistical, structural and syntactic, and discusses their merits and demerits considering the context. Through comprehensive experiments, it also explores whether these approaches can be combined. The book presents research problems, state-of-the-art methods that convey basic steps as well as prominent techniques, evaluation metrics and protocols, and research standpoints/directions that are associated with it. However, it is not limited to straightforward isolated graphics (visual patterns) recognition; it also addresses complex and composite graphical symbols recognition, which is motivated by real-world industrial problems.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Author: Alvaro Pardo
Publisher: Springer
Total Pages: 795
Release: 2015-10-24
Genre: Computers
ISBN: 331925751X

This book constitutes the refereed proceedings of the 20th Iberoamerican Congress on Pattern Recognition, CIARP 2015, held in Montevideo, Uruguay, in November 2015. The 95 papers presented were carefully reviewed and selected from 185 submissions. The papers are organized in topical sections on applications on pattern recognition; biometrics; computer vision; gesture recognition; image classification and retrieval; image coding, processing and analysis; segmentation, analysis of shape and texture; signals analysis and processing; theory of pattern recognition; video analysis, segmentation and tracking.

Decision Forests for Computer Vision and Medical Image Analysis

Decision Forests for Computer Vision and Medical Image Analysis
Author: Antonio Criminisi
Publisher: Springer Science & Business Media
Total Pages: 367
Release: 2013-01-30
Genre: Computers
ISBN: 1447149297

This practical and easy-to-follow text explores the theoretical underpinnings of decision forests, organizing the vast existing literature on the field within a new, general-purpose forest model. Topics and features: with a foreword by Prof. Y. Amit and Prof. D. Geman, recounting their participation in the development of decision forests; introduces a flexible decision forest model, capable of addressing a large and diverse set of image and video analysis tasks; investigates both the theoretical foundations and the practical implementation of decision forests; discusses the use of decision forests for such tasks as classification, regression, density estimation, manifold learning, active learning and semi-supervised classification; includes exercises and experiments throughout the text, with solutions, slides, demo videos and other supplementary material provided at an associated website; provides a free, user-friendly software library, enabling the reader to experiment with forests in a hands-on manner.

Handbook of Document Image Processing and Recognition

Handbook of Document Image Processing and Recognition
Author: David Doermann
Publisher: Springer
Total Pages: 1055
Release: 2014-05-22
Genre: Computers
ISBN: 9780857298607

The Handbook of Document Image Processing and Recognition is a comprehensive resource on the latest methods and techniques in document image processing and recognition. Each chapter provides a clear overview of the topic followed by the state of the art of techniques used – including elements of comparison between them – along with supporting references to archival publications, for those interested in delving deeper into topics addressed. Rather than favor a particular approach, the text enables the reader to make an informed decision for their specific problems.