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Soft Computing for Recognition based on Biometrics

  • Book
  • © 2010

Overview

Editors:
  1. Patricia Melin

    1. Tijuana Institute of Technology, Chula Vista, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Janusz Kacprzyk

    1. Polish Academy of Sciences, Warsaw, Poland

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    You can also search for this editor in PubMed   Google Scholar

  3. Witold Pedrycz

    1. University of Alberta, Edmonton, Canada

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  • Recent research in Soft Computing for Recognition based on Biometrics
  • Carefully edited book
  • Written by experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 312)

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Table of contents (27 chapters)

  1. Front Matter

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  2. Classification Algorithms and Applications

    1. Front Matter

      Pages 1-1
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    2. Soft Computing Approaches to the Problem of Infant Cry Classification with Diagnostic Purposes

      • Carlos A. Reyes-Garcia, Orion F. Reyes-Galaviz, Sergio D. Cano-Ortiz, Daniel I. Escobedo-Becerro, Ramón Zatarain, Lucia Barrón-Estrada
      Pages 3-18

    3. Neural Networks and SVM-Based Classification of Leukocytes Using the Morphological Pattern Spectrum

      • Juan Manuel Ramirez-Cortes, Pilar Gomez-Gil, Vicente Alarcon-Aquino, Jesus Gonzalez-Bernal, Angel Garcia-Pedrero
      Pages 19-35

    4. Hybrid System for Cardiac Arrhythmia Classification with Fuzzy K-Nearest Neighbors and Neural Networks Combined by a Fuzzy Inference System

      • Eduardo Ramírez, Oscar Castillo, José Soria
      Pages 37-55

    5. A Comparative Study of Blog Comments Spam Filtering with Machine Learning Techniques

      • Christian Romero, Mario Garcia-Valdez, Arnulfo Alanis
      Pages 57-72

    6. Distributed Implementation of an Intelligent Data Classifier

      • Victor J. Sosa-Sosa, Ivan Lopez-Arevalo, Omar Jasso-Luna, Hector Fraire-Huacuja
      Pages 73-82

  3. Pattern Recognition

    1. Front Matter

      Pages 83-83
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    2. Modular Neural Network with Fuzzy Integration and Its Optimization Using Genetic Algorithms for Human Recognition Based on Iris, Ear and Voice Biometrics

      • Daniela Sánchez, Patricia Melin
      Pages 85-102

    3. Comparative Study of Type-2 Fuzzy Inference System Optimization Based on the Uncertainty of Membership Functions

      • Denisse Hidalgo, Patricia Melin, Oscar Castillo, Guillermo Licea
      Pages 103-120

    4. Modular Neural Network for Human Recognition from Ear Images Using Wavelets

      • Lizette Gutiérrez, Patricia Melin, Miguel López
      Pages 121-135

    5. Modular Neural Networks for Person Recognition Using the Contour Segmentation of the Human Iris Biometric Measurement

      • Fernando Gaxiola, Patricia Melin, Miguel López
      Pages 137-153

    6. Real Time Face Identification Using a Neural Network Approach

      • Juan Carlos Vázquez, Miguel López, Patricia Melin
      Pages 155-169

    7. Comparative Study of Feature Extraction Methods of Fuzzy Logic Type 1 and Type-2 for Pattern Recognition System Based on the Mean Pixels

      • Miguel Lopez, Patricia Melin, Oscar Castillo
      Pages 171-188

  4. Optimization Methods

    1. Front Matter

      Pages 189-189
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    2. Application of the Bee Swarm Optimization BSO to the Knapsack Problem

      • Marco Aurelio Sotelo-Figueroa, Rosario Baltazar, Martín Carpio
      Pages 191-206

    3. An Approach Based on Neural Networks for Gas Lift Optimization

      • Jose A. Ruz-Hernandez, Ruben Salazar-Mendoza, Guillermo Jimenez de la C., Ramon Garcia-Hernandez, Evgen Shelomov
      Pages 207-224

    4. A New Evolutionary Method with Particle Swarm Optimization and Genetic Algorithms Using Fuzzy Systems to Dynamically Parameter Adaptation

      • Fevrier Valdez, Patricia Melin
      Pages 225-243

    5. Local Survival Rule for Steer an Adaptive Ant-Colony Algorithm in Complex Systems

      • Claudia Gómez Santillán, Laura Cruz Reyes, Elisa Schaeffer, Eustorgio Meza, Gilberto Rivera Zarate
      Pages 245-265

    6. Using Consecutive Swaps to Explore the Insertion Neighborhood in Tabu Search Solution of the Linear Ordering Problem

      • Francisco Eduardo Gosch Ingram, Guadalupe Castilla Valdez, Héctor Joaquín Fraire Huacuja
      Pages 267-276
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Keywords

About this book

We describe in this book, bio-inspired models and applications of hybrid intel- gent systems using soft computing techniques for image analysis and pattern r- ognition based on biometrics and other information sources. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of classification methods and applications, which are basically papers that propose new models for classification to solve general pr- lems and applications. The second part contains papers with the main theme of modular neural networks in pattern recognition, which are basically papers using bio-inspired techniques, like modular neural networks, for achieving pattern r- ognition based on biometric measures. The third part contains papers with the theme of bio-inspired optimization methods and applications to diverse problems. The fourth part contains papers that deal with general theory and algorithms of bio-inspired methods, like neural networks and evolutionary algorithms. The fifth part contains papers on computer vision applications of soft computing methods. In the part of classification methods and applications there are 5 papers that - scribe different contributions on fuzzy logic and bio-inspired models with appli- tion in classification for medical images and other data.

Editors and Affiliations

  • Tijuana Institute of Technology, Chula Vista, USA

    Patricia Melin

  • Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  • University of Alberta, Edmonton, Canada

    Witold Pedrycz

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