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Logo Recognition

Author: Jingying Chen
Publisher: CRC Press
ISBN: 1439847851
Size: 64.77 MB
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Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos. Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy conditions. Beginning with an introduction to fundamental concepts and methods in pattern and shape recognition, it surveys advances in logo recognition. The authors also propose a new logo recognition system that can be used under adverse conditions such as broken lines, added noise, and occlusion. The proposed system introduces a novel polygonal approximation, a robust indexing scheme, and a new line segment Hausdorff distance (LHD) matching method that can handle more distortion and transformation types than previous techniques. In the first stage, raw logos are transformed into normalized line segment maps. In the second stage, effective line pattern features are used to index the database to generate a moderate number of likely models. In the third stage, an improved LHD measure screens and generates the best matches. A comprehensive overview of logo recognition, the book also presents successful applications of the technology and suggests directions for future research.

Face Detection And Recognition

Author: Asit Kumar Datta
Publisher: CRC Press
ISBN: 148222657X
Size: 51.40 MB
Format: PDF, Docs
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Face detection and recognition are the nonintrusive biometrics of choice in many security applications. Examples of their use include border control, driver’s license issuance, law enforcement investigations, and physical access control. Face Detection and Recognition: Theory and Practice elaborates on and explains the theory and practice of face detection and recognition systems currently in vogue. The book begins with an introduction to the state of the art, offering a general review of the available methods and an indication of future research using cognitive neurophysiology. The text then: Explores subspace methods for dimensionality reduction in face image processing, statistical methods applied to face detection, and intelligent face detection methods dominated by the use of artificial neural networks Covers face detection with colour and infrared face images, face detection in real time, face detection and recognition using set estimation theory, face recognition using evolutionary algorithms, and face recognition in frequency domain Discusses methods for the localization of face landmarks helpful in face recognition, methods of generating synthetic face images using set estimation theory, and databases of face images available for testing and training systems Features pictorial descriptions of every algorithm as well as downloadable source code (in MATLAB®/PYTHON) and hardware implementation strategies with code examples Demonstrates how frequency domain correlation techniques can be used supplying exhaustive test results Face Detection and Recognition: Theory and Practice provides students, researchers, and practitioners with a single source for cutting-edge information on the major approaches, algorithms, and technologies used in automated face detection and recognition.

Plan Activity And Intent Recognition

Author: Gita Sukthankar
Publisher: Newnes
ISBN: 012401710X
Size: 14.79 MB
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Plan recognition, activity recognition, and intent recognition together combine and unify techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning. Plan, Activity, and Intent Recognition explains the crucial role of these techniques in a wide variety of applications including: personal agent assistants computer and network security opponent modeling in games and simulation systems coordination in robots and software agents web e-commerce and collaborative filtering dialog modeling video surveillance smart homes In this book, follow the history of this research area and witness exciting new developments in the field made possible by improved sensors, increased computational power, and new application areas. Combines basic theory on algorithms for plan/activity recognition along with results from recent workshops and seminars Explains how to interpret and recognize plans and activities from sensor data Provides valuable background knowledge and assembles key concepts into one guide for researchers or students studying these disciplines

Template Matching Techniques In Computer Vision

Author: Roberto Brunelli
Publisher: John Wiley & Sons
ISBN: 9780470744048
Size: 63.32 MB
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The detection and recognition of objects in images is a key research topic in the computer vision community. Within this area, face recognition and interpretation has attracted increasing attention owing to the possibility of unveiling human perception mechanisms, and for the development of practical biometric systems. This book and the accompanying website, focus on template matching, a subset of object recognition techniques of wide applicability, which has proved to be particularly effective for face recognition applications. Using examples from face processing tasks throughout the book to illustrate more general object recognition approaches, Roberto Brunelli: examines the basics of digital image formation, highlighting points critical to the task of template matching; presents basic and advanced template matching techniques, targeting grey-level images, shapes and point sets; discusses recent pattern classification paradigms from a template matching perspective; illustrates the development of a real face recognition system; explores the use of advanced computer graphics techniques in the development of computer vision algorithms. Template Matching Techniques in Computer Vision is primarily aimed at practitioners working on the development of systems for effective object recognition such as biometrics, robot navigation, multimedia retrieval and landmark detection. It is also of interest to graduate students undertaking studies in these areas.

Object Detection And Recognition In Digital Images

Author: Boguslaw Cyganek
Publisher: John Wiley & Sons
ISBN: 111861836X
Size: 47.89 MB
Format: PDF
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Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications. Places an emphasis on tensor and statistical based approaches within object detection and recognition. Provides an overview of image clustering and classification methods which includes subspace and kernel based processing, mean shift and Kalman filter, neural networks, and k-means methods. Contains numerous case study examples of mainly automotive applications. Includes a companion website hosting full C++ implementation, of topics presented in the book as a software library, and an accompanying manual to the software platform.

Machine Learning For Human Motion Analysis Theory And Practice

Author: Wang, Liang
Publisher: IGI Global
ISBN: 1605669016
Size: 34.30 MB
Format: PDF
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"This book highlights the development of robust and effective vision-based motion understanding systems, addressing specific vision applications such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval"--Provided by publisher.

Character Recognition Systems

Author: Mohamed Cheriet
Publisher: John Wiley & Sons
ISBN: 9780470176528
Size: 65.95 MB
Format: PDF, Mobi
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"Much of pattern recognition theory and practice, including methods such as Support Vector Machines, has emerged in an attempt to solve the character recognition problem. This book is written by very well-known academics who have worked in the field for many years and have made significant and lasting contributions. The book will no doubt be of value to students and practitioners." -Sargur N. Srihari, SUNY Distinguished Professor, Department of Computer Science and Engineering, and Director, Center of Excellence for Document Analysis and Recognition (CEDAR), University at Buffalo, The State University of New York "The disciplines of optical character recognition and document image analysis have a history of more than forty years. In the last decade, the importance and popularity of these areas have grown enormously. Surprisingly, however, the field is not well covered by any textbook. This book has been written by prominent leaders in the field. It includes all important topics in optical character recognition and document analysis, and is written in a very coherent and comprehensive style. This book satisfies an urgent need. It is a volume the community has been awaiting for a long time, and I can enthusiastically recommend it to everybody working in the area." -Horst Bunke, Professor, Institute of Computer Science and Applied Mathematics (IAM), University of Bern, Switzerland In Character Recognition Systems, the authors provide practitioners and students with the fundamental principles and state-of-the-art computational methods of reading printed texts and handwritten materials. The information presented is analogous to the stages of a computer recognition system, helping readers master the theory and latest methodologies used in character recognition in a meaningful way. This book covers: * Perspectives on the history, applications, and evolution of Optical Character Recognition (OCR) * The most widely used pre-processing techniques, as well as methods for extracting character contours and skeletons * Evaluating extracted features, both structural and statistical * Modern classification methods that are successful in character recognition, including statistical methods, Artificial Neural Networks (ANN), Support Vector Machines (SVM), structural methods, and multi-classifier methods * An overview of word and string recognition methods and techniques * Case studies that illustrate practical applications, with descriptions of the methods and theories behind the experimental results Each chapter contains major steps and tricks to handle the tasks described at-hand. Researchers and graduate students in computer science and engineering will find this book useful for designing a concrete system in OCR technology, while practitioners will rely on it as a valuable resource for the latest advances and modern technologies that aren't covered elsewhere in a single book.

Hybrid Artificial Intelligent Systems

Author: Francisco Martínez-Álvarez
Publisher: Springer
ISBN: 3319320343
Size: 42.86 MB
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This volume constitutes the refereed proceedings of the 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, held in Seville, Spain, in April 2016. The 63 full papers published in this volume were carefully reviewed and selected from 150 submissions. They are organized in topical sections on data mining and knowledge discovery; time series; bio-inspired models and evolutionary computation; learning algorithms; video and image; classification and cluster analysis; applications; bioinformatics; and hybrid intelligent systems for data mining and applications.

Consumer Brand Relationships

Author: Susan Fournier
Publisher: Routledge
ISBN: 1136470972
Size: 23.59 MB
Format: PDF, Kindle
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The creation and management of customer relationships is fundamental to the practice of marketing. Marketers have long maintained a keen interest in relationships: what they are, why they are formed, what effects they have on consumers and the marketplace, how they can be measured and when and how they evolve and decline. While marketing research has a long tradition in the study of business relationships between manufacturers and suppliers and buyers and sellers, attention in the past decade has expanded to the relationships that form between consumers and their brands (such as products, stores, celebrities, companies or countries). The aim of this book is to advance knowledge about consumer-brand relationships by disseminating new research that pushes beyond theory, to applications and practical implications of brand relationships that businesses can apply to their own marketing strategies. With contributions from an impressive array of scholars from around the world, this volume will provide students and researchers with a useful launch pad for further research in this blossoming area.