Image recognition systems

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  • Image recognition and classification is one of the most actively pursued areas in the broad field of imaging sciences and engineering. The reason is evident: the ability to replace human visual capabilities with a machine is very important and there are diverse applications. The main idea is to inspect an image scene by processing data obtained from sensors.

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  • Details the latest image processing algorithms and imaging systems for image recognition with diverse applications to the military; the transportation, aerospace, information security, and biomedical industries; radar systems; and image tracking systems.This book presents important recent advances in sensors, image processing algorithms, and systems for image recognition and classification with diverse applications in military, aerospace, security, image tracking, radar, biomedical, and intelligent transportation.

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  • The purpose of this book, entitled Face Analysis, Modeling and Recognition Systems is to provide a concise and comprehensive coverage of artificial face recognition domain across four major areas of interest: biometrics, robotics, image databases and cognitive models. Our book aims to provide the reader with current state-of-the-art in these domains. The book is composed of 12 chapters which are grouped in four sections.

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  • Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008, Article ID 468693, 7 pages doi:10.1155/2008/468693 Research Article Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition J. Uglov, L. Jakaite, V. Schetinin, and C. Maple Computing and Information System Department, University of Bedfordshire, Luton LU1 3JU, UK Correspondence should be addressed to V. Schetinin, Received 16 June 2007; Revised 28 August 2007; Accepted 19 November 2007 Recommended by Konstantinos N.

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  • Character recognition is one of the pattern recognition technologies that are most widely used in practical applications. This book presents recent advances that are relevant to character recognition, from technical topics such as image processing, feature extraction or classification, to new applications including human-computer interfaces. The goal of this book is to provide a reference source for academic research and for professionals working in the character recognition field.

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  • 8. OBJECT RECOGNITION 8.1 Introduction An object recognition system finds objects in the real world from an image of the world, using object models which are known a priori. This task is surprisingly difficult. In this chapter we will discuss

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  • In the last two decades, fractional (or non integer) differentiation has played a very important role in various fields such as mechanics, electricity, chemistry, biology, economics, control theory and signal and image processing. For example, in the last three fields, some important considerations such as modelling, curve fitting, filtering, pattern recognition, edge detection, identification, stability, controllability, observability and robustness are now linked to long-range dependence phenomena. Similar progress has been made in other fields listed here.

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  • Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, Blind Source Separation (BSS) by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, image processing, telecommunications, medical signal processing and several data mining issues.

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  • EURASIP Journal on Applied Signal Processing 2003:9, 890–901 c 2003 Hindawi Publishing Corporation An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System Javad Haddadnia Engineering Department, Tarbiat Moallem University of Sabzevar, Sabzevar, Khorasan 397, Iran Email: Majid Ahmadi Electrical and Computer Engineering Department, University of Windsor, Windsor, Ontario, Canada N9B 3P4 Email: ahmadi@uwindsor.

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  • Optical Character Recognition is a technology that enable human to digitize scanned images, converting into editable text on the computer and increasing the speed of data transmission directly into computer from many source of documents. In addition, it is also useful in handwriting recognition and making digital images searchable for text. In this paper, we proposed anOCR system which is capable of recognizing Vietnamese characters fortyped texts using template matching and artificial neural network recognizing methods.

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  • SHAPE ANALYSIS Several qualitative and quantitative techniques have been developed for characterizing the shape of objects within an image. These techniques are useful for classifying objects in a pattern recognition system and for symbolically describing objects in an image understanding system. Some of the techniques apply only to binary-valued images; others can be extended to gray level images.

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  • We present a portable translator that recognizes and translates phrases on signboards and menus as captured by a builtin camera. This system can be used on PDAs or mobile phones and resolves the difficulty of inputting some character sets such as Japanese and Chinese if the user doesn’t know their readings. Through the high speed mobile network, small images of signboards can be quickly sent to the recognition and translation server.

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