A Brain-Inspired Visual Pattern Recognition Architecture and Its Applications

A Brain-Inspired Visual Pattern Recognition Architecture and Its Applications

Fok Hing Chi Tivive (University of Wollongong, Australia) and Abdesselam Bouzerdoum (University of Wollongong, Australia)
Copyright: © 2008 |Pages: 21
DOI: 10.4018/978-1-59904-807-9.ch011
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With the ever-increasing utilization of imagery in scientific, industrial, civilian, and military applications, visual pattern recognition has been thriving as a research field and has become an essential enabling technology for many applications. In this chapter, we present a brain-inspired pattern recognition architecture that can easily be adapted to solve various real-world visual pattern recognition tasks. The architecture has the ability to extract visual features from images and classify them within the same network structure; in other words, it integrates the feature extraction stage with the classification stage, and both stages are optimized with respect to one another. The main processing unit for feature extraction is governed by a nonlinear biophysical mechanism known as shunting inhibition, which plays a significant role in visual information processing in the brain. Here, the proposed architecture is applied to four real-world visual pattern recognition problems; namely, handwritten digit recognition, texture segmentation, automatic face detection, and gender recognition. Experimental results demonstrate that the proposed architecture is very competitive with and sometimes outperforms existing state-of-the-art techniques for each application.

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Table of Contents
Brijesh Verma, Michael Blumenstein
Brijesh Verma, Michael Blumenstein
Chapter 1
Brijesh Verma, Michael Blumenstein
Cursive handwriting recognition is a challenging task for many real-world applications such as document authentication, form processing, postal... Sample PDF
Fusion of Segmentation Strategies for Off-Line Cursive Handwriting Recognition
Chapter 2
Seiichi Uchida
This chapter reviews various elastic matching techniques for handwritten character recognition. Elastic matching is formulated as an optimization... Sample PDF
Elastic Matching Techniques for Handwritten Character Recognition
Chapter 3
Luana Batista, Dominique Rivard, Robert Sabourin, Eric Granger, Patrick Maupin
Automatic signature verification is a biometric method that can be applied in all situations where handwritten signatures are used, such as cashing... Sample PDF
State of the Art in Off-Line Signature Verification
Chapter 4
Vamsi Krishna Madasu, Brian C. Lovell
This chapter presents an off-line signature verification and forgery detection system based on fuzzy modeling. The various handwritten signature... Sample PDF
An Automatic Off-Line Signature Verification and Forgery Detection System
Chapter 5
Sergio Suárez-Guerra, Jose Luis Oropeza-Rodriguez
This chapter presents the state-of-the-art automatic speech recognition (ASR) technology, which is a very successful technology in the computer... Sample PDF
Introduction to Speech Recognition
Chapter 6
Graham Leedham, Vladimir Pervouchine, Haishan Zhong
This chapter examines features of handwriting and speech and their effectiveness at determining whether the identity of a writer or speaker can be... Sample PDF
Seeking Patterns in the Forensic Analysis of Handwriting and Speech
Chapter 7
Donggang Yu, Tuan D. Pham
This chapter describes a new pattern recognition method: pattern recognition-based morphological structure. First, smooth following and... Sample PDF
Image Pattern Recognition-Based Morphological Structure and Applications
Chapter 8
Ting Shan, Abbas Bigdeli, Brian C. Lovell, Shaokang Chen
In this chapter, we propose a pose variability compensation technique, which synthesizes realistic frontal face images from nonfrontal views. It is... Sample PDF
Robust Face Recognition Technique for a Real-Time Embedded Face Recognition System
Chapter 9
Prithwijit Guha, Amitabha Mukerjee, K. S. Venkatesh
Complex multiobject interactions result in occlusion sequences, which are a visual signature for the event. In this work, multiobject interactions... Sample PDF
Occlusion Sequence Mining for Activity Discovery from Surveillance Videos
Chapter 10
Hui-Xing Jia, Yu-Jin Zhang
Human detection is the first step for a number of applications such as smart video surveillance, driving assistance systems, and intelligent digital... Sample PDF
Human Detection in Static Images
Chapter 11
Fok Hing Chi Tivive, Abdesselam Bouzerdoum
With the ever-increasing utilization of imagery in scientific, industrial, civilian, and military applications, visual pattern recognition has been... Sample PDF
A Brain-Inspired Visual Pattern Recognition Architecture and Its Applications
Chapter 12
Mariusz Rawski, Henry Selvaraj, Bogdan J. Falkowski, Tadeusz Luba
This chapter, taking FIR filters as an example, presents the discussion on efficiency of different implementation methodologies of DSP algorithms... Sample PDF
Significance of Logic Synthesis in FPGA-Based Design of Image and Signal Processing Systems
Chapter 13
Nina Zhou, Lipo Wang
This chapter introduces an approach to class-dependent feature selection and a novel support vector machine (SVM). The relative background and... Sample PDF
A Novel Support Vector Machine with Class-Dependent Features for Biomedical Data
Chapter 14
Alistair Shilton, Marimuthu Palaniswami
This chapter presents a unified introduction to support vector machine (SVM) methods for binary classification, one-class classification, and... Sample PDF
A Unified Approach to Support Vector Machines
Chapter 15
Katti Faceli, Andre C.P.L.F. de Carvalho, Marcilio C.P. de Souto
Clustering is an important tool for data exploration. Several clustering algorithms exist, and new algorithms are frequently proposed in the... Sample PDF
Cluster Ensemble and Multi-Objective Clustering Methods
Chapter 16
Peter Duell, Xin Yao
Negative correlation learning (NCL) is a technique that attempts to create an ensemble of neural networks whose outputs are accurate but negatively... Sample PDF
Implementing Negative Correlation Learning in Evolutionary Ensembles with Suitable Speciation Techniques
Chapter 17
Toshio Tsuji, Nan Bu, Osamu Fukuda
In the field of pattern recognition, probabilistic neural networks (PNNs) have been proven as an important classifier. For pattern recognition of... Sample PDF
A Recurrent Probabilistic Neural Network for EMG Pattern Recognition
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