Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies

Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies

Vijay Kumar Mago, Nitin Bhatia

Copyright: © 2012 |Pages: 786

ISBN13: 9781613504291|ISBN10: 1613504292|EISBN13: 9781613504307

DOI: 10.4018/978-1-61350-429-1

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MLA

Mago, Vijay Kumar, and Nitin Bhatia, editors. Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies. IGI Global, 2012. https://doi.org/10.4018/978-1-61350-429-1

APA

Mago, V. K. & Bhatia, N. (Eds.). (2012). Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies. IGI Global. https://doi.org/10.4018/978-1-61350-429-1

Chicago

Mago, Vijay Kumar, and Nitin Bhatia, eds. Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-429-1

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The need for intelligent machines in areas such as medical diagnostics, biometric security systems, and image processing motivates researchers to develop and explore new techniques, algorithms, and applications in this evolving field.

Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies provides a common platform for researchers to present theoretical and applied research findings for enhancing and developing intelligent systems. Through its discussions of advances in and applications of pattern recognition technologies and artificial intelligence, this reference highlights core concepts in biometric imagery, feature recognition, and other related fields, along with their applicability.

Table of Contents

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Front Materials

Title Page

Copyright Page

Editorial Advisory Board

Preface

Chapters

Chapter 1

From Object Recognition to Object Localization (pages 1-17)

Rigas Kouskouridas, Antonios Gasteratos

Recognizing objects in a scene is a fundamental task in image understanding. The recent advances in robotics and related technologies have placed more challenges and stricter requirements to this issue. In such applications, robots...

Chapter 2

A Multi-Linear Statistical Method for Discriminant Analysis of 2D Frontal Face Images (pages 18-33)

Carlos Eduardo Thomaz, Vagner do Amaral, Gilson Antonio Giraldi, Edson Caoru Kitani, João Ricardo Sato, Duncan Gillies

This chapter describes a multi-linear discriminant method of constructing and quantifying statistically significant changes on human identity photographs. The approach is based on a general multivariate two-stage linear framework...

Chapter 3

Orthogonal Image Moment Invariants: Highly Discriminative Features for Pattern Recognition Applications (pages 34-52)

G.A. Papakostas, E.G. Karakasis, D.E. Koulouriotis

This chapter focuses on the usage of image orthogonal moments as discrimination features in pattern recognition applications and discusses their main properties. Initially, the ability of the moments to carry information of an image...

Chapter 4

Certain and Uncertain Triangulation in Multiple Camera Vision Systems via LMIs (pages 53-64)

Graziano Chesi, Yeung Sam Hung

Triangulation is a fundamental problem in computer vision that consists of estimating the 3D position of a point of the scene from the estimates of its image projections on some cameras and from the estimates of the projection...

Chapter 5

Camera Calibration with 1D Objects (pages 65-85)

José Alexandre de França, Marcelo Ricardo Stemmer, Maria B. de Morais França, Rodrigo H. Cunha Palácios

Camera calibration is a process that allows to fully understand how the camera forms the image. It is necessary especially when 3D information of the scene must be known. Calibration can be performed using a 1D pattern (points on a...

Chapter 6

Object Segmentation Based on a Nonparametric Snake with Motion Prediction in Video (pages 86-107)

Sang-Myoung Ye, Rae-Hong Park, Dong-Kyu Lee

Object segmentation in video sequence is a basic and important task in video applications such as surveillance systems and video coding. Nonparametric snake algorithms for object segmentation have been proposed to overcome the...

Chapter 7

Analysis of Face Space for Recognition using Interval-Valued Subspace Technique (pages 108-127)

C.J. Prabhakar

The major contribution of the research work presented in this chapter is the development of effective face recognition algorithm using analysis of face space in the interval-valued subspace. The analysis of face images is used for...

Chapter 8

Object Recognition with a Limited Database Using Shape Space Theory (pages 128-147)

Yuexing Han, Bing Wang, Hideki Koike, Masanori Idesawa

One of the main goals of image understanding and computer vision applications is to recognize an object from various images. Object recognition has been deeply developed for the last three decades, and a lot of approaches have been...

Chapter 9

Efficient Iris Identification with Improved Segmentation Techniques (pages 148-164)

Abhishek Verma, Chengjun Liu

In this chapter, the authors propose and implement an improved iris recognition method based on image enhancement and heuristics. They make major improvements in the iris segmentation phase. In particular, the authors implement the...

Chapter 10

Color Image Segmentation of Endoscopic and Microscopic Images for Abnormality Detection in Esophagus (pages 165-193)

P. S. Hiremath, Iranna Y. Humnabad

The study of medical image analysis encompasses the various techniques for acquisition of images of biological structures pertaining to human body using radiations in different frequency ranges. The advancements in medical imaging...

Chapter 11

Adaptive Face Recognition of Partially Visible Faces (pages 194-211)

T. Ravindra Babu, Chethan S.A. Danivas, S.V. Subrahmanya

Face Recognition is an active research area. In many practical scenarios, when faces are acquired without the cooperation or knowledge of the subject, they are likely to get occluded. Apart from image background, pose, illumination...

Chapter 12

Facial Muscle Activity Patterns for Recognition of Utterances in Native and Foreign Language: Testing for its Reliability and Flexibility (pages 212-231)

Sridhar Arjunan, Dinesh Kant Kumar, Hans Weghorn, Ganesh Naik

The need for developing reliable and flexible human computer interface is increased and applications of HCI have been in each and every field. Human factors play an important role in these kinds of interfaces. Research and...

Chapter 13

Feature Set Reduction in Rotation Invariant CBIR Using Dual-Tree Complex Wavelet Transform (pages 232-248)

Deepak Sharma, Ekta Walia, H.P. Sinha

An accurate Content Based Image Retrieval (CBIR) system is essential for the correct retrieval of desired images from the underlying database. Rotation invariance is very important for accurate Content Based Image Retrieval (CBIR)....

Chapter 14

Devnagari Script Recognition: Techniques and Challenges (pages 249-269)

P. Mukherji, P.P. Rege

Devnagari script is the most widely used script in India and its Optical Character Recognition (OCR) poses many challenges. Handwritten script has many variations, and existing methods used are discussed. The authors have also...

Chapter 15

Corner Detection Using Fuzzy Principles (pages 270-285)

Erik Cuevas, Daniel Zaldivar, Marco Perez-Cisneros

Reliable corner detection is an important task in pattern recognition applications. In this chapter an approach based on fuzzy-rules to detect corners even under imprecise information is presented. The uncertainties arising due to...

Chapter 16

Eye Detection Using Color, Haar Features, and Efficient Support Vector Machine (pages 286-309)

Shuo Chen, Chengjun Liu

Eye detection is an important initial step in an automatic face recognition system. Though numerous eye detection methods have been proposed, many problems still exist, especially in the detection accuracy and efficiency under...

Chapter 17

Emotion Recognition from Facial Expression and Electroencephalogram Signals (pages 310-337)

Amit Konar, Aruna Chakraborty, Pavel Bhowmik, Sauvik Das, Anisha Halder

This chapter proposes new approaches to emotion recognition from facial expression and electroencephalogram signals. Subjects are excited with selective audio-visual stimulus, responsible for arousal of specific emotions....

Chapter 18

Detecting Eyes and Lips Using Neural Networks and SURF Features (pages 338-354)

Artem A. Lenskiy, Jong-Soo Lee

In this chapter, the authors elaborate on the facial image segmentation and the detection of eyes and lips using two neural networks. The first neural network is applied to segment skin-colors and the second to detect facial...

Chapter 19

Classification with Axis-Aligned Rectangular Boundaries (pages 355-366)

Sung Hee Park

This chapter presents a new method for binary classification that classifies input data into two regions separated by axis-aligned rectangular boundaries. Given the number of rectangular regions to use, this algorithm automatically...

Chapter 20

ICA as Pattern Recognition Technique for Gesture Identification: A Study Using Bio-Signal (pages 367-387)

Ganesh Naik, Dinesh Kant Kumar, Sridhar Arjunan

In recent times there is an urgent need for a simple yet robust system to identify natural hand actions and gestures for controlling prostheses and other computer assisted devices. Surface Electromyogram (sEMG) is a non-invasive...

Chapter 21

Fuzzy Methods of Multiple-Criteria Evaluation and Their Software Implementation (pages 388-411)

Pavel Holecek, Jana Talašová, Ivo Müller

This chapter describes a system of fuzzy methods designed to solve a broad range of problems in multiple-criteria evaluation, and also their software implementation, FuzzME. A feature common to all the presented methods is the type...

Chapter 22

Realizing Interval Type-2 Fuzzy Systems with Type-1 Fuzzy Systems (pages 412-427)

Mamta Khosla, R K Sarin, Moin Uddin, Satvir Singh, Arun Khosla

In this chapter, the authors have realized Interval Type-2 Fuzzy Logic Systems (IT2 FLSs) with the average of two Type-1 Fuzzy Logic Systems (T1 FLSs). The authors have presented two case studies by applying this realization...

Chapter 23

Comparative Analysis of Random Forests with Statistical and Machine Learning Methods in Predicting Fault-Prone Classes (pages 428-449)

Ruchika Malhotra, Arvinder Kaur, Yogesh Singh

There are available metrics for predicting fault prone classes, which may help software organizations for planning and performing testing activities. This may be possible due to proper allocation of resources on fault prone parts of...

Chapter 24

Neural Networks: Evolution, Topologies, Learning Algorithms and Applications (pages 450-498)

Siddhartha Bhattacharyya

These networks generally operate in two different modes, viz., supervised and unsupervised modes. The supervised mode of operation requires a supervisor to train the network with a training set of data. Networks operating in...

Chapter 25

A New Optimization Approach to Clustering Fuzzy Data for Type-2 Fuzzy System Modeling (pages 499-508)

Mohammad Hossein Fazel Zarandi, Milad Avazbeigi

This chapter presents a new optimization method for clustering fuzzy data to generate Type-2 fuzzy system models. For this purpose, first, a new distance measure for calculating the (dis)similarity between fuzzy data is proposed....

Chapter 26

Estimation of MIMO Wireless Channels Using Artificial Neural Networks (pages 509-543)

Kandarpa Kumar Sarma, Abhijit Mitra

Artificial Neural Network (ANN) is a non-parametric statistical tool which can be used for a host of pattern classification and prediction problems. It has excelled in diverse areas of application ranging from character recognition...

Chapter 27

A Novel 3D Approach for Patient Schedule Using Multi-Agent Coordination (pages 544-563)

E. Grace Mary Kanaga, M.L. Valarmathi, Preethi S.H. Darius

This chapter presents a novel 3D approach for patient scheduling (3D-PS) using multi-agents. Here the 3Ds refers to the Distributed, Dynamic and Decentralized nature of the patient scheduling. As in many other scheduling problems, in...

Chapter 28

A Fuzzy Approach to Disaster Modeling: Decision Making Support and Disaster Management Tool for Emergency Medical Rescue Services (pages 564-582)

Jan Stoklasa

The decision making process of the Emergency Medical Rescue Services (EMRS) operations centre during disasters involves a significant amount of uncertainty. Decisions need to be made quickly, and no mistakes are tolerable...

Chapter 29

Fuzzy Cognitive Map Reasoning Mechanism for Handling Uncertainty and Missing Data: Application in Medical Diagnosis (pages 583-608)

Elpiniki I. Papageorgiou

In this study, the fuzzy causal map inference mechanisms are analyzed for decision making tasks and a comparative analysis is performed to handle with the uncertainty in the problem of pulmonary risk prediction. Fuzzy Cognitive...

Chapter 30

On the Use of Fuzzy Logic in Electronic Marketplaces (pages 609-632)

Kostas Kolomvatsos, Stathes Hadjiefthymiades

Today, there is a large number of product providers in the Web. Electronic Marketplaces (EMs) enable entities to negotiate and trade products. Usually, intelligent agents assume the responsibility of representing buyers or sellers in...

Chapter 31

A Neuro-Fuzzy Expert System Trained by Particle Swarm Optimization for Stock Price Prediction (pages 633-650)

Mohammad Hossein Fazel Zarandi, Milad Avazbeigi, Meysam Alizadeh

In today’s competitive markets, prediction of financial variables has become a critical issue. Especially in stock market analysis where a wrong prediction may result in a big loss in terms of time and money, having a robust...

Chapter 32

Hand Tremor Prediction and Classification Using Electromyogram Signals to Control Neuro-Motor Instability (pages 651-673)

Koushik Bakshi, Sourav Chandra, Amit Konar, D.N. Tibarewala

This chapter provides a prototype design of a hand tremor compensator/controller to reduce the effect of the tremor to an external device/ apparatus, such as a magnetic pen for the patients suffering from Parkinson and similar...

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