Ear Recognition by Using Self Organizing Feature Map

A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else.The aim of the w...

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Main Author: Suad K. Mohammad
Format: Article
Language:English
Published: Unviversity of Technology- Iraq 2013-07-01
Series:Engineering and Technology Journal
Subjects:
Online Access:https://etj.uotechnology.edu.iq/article_82289_be6ef8f293a9f61db6084b01013b9480.pdf
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author Suad K. Mohammad
author_facet Suad K. Mohammad
author_sort Suad K. Mohammad
collection DOAJ
description A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else.The aim of the work presented within this paper is to develop an optimum image compression system using haar wavelet transform and a neural network. In this paper we have developed and illustrated a recognition system for human ears using a Kohonen self-organizing map (SOM) or Self-Organizing Feature Map (SOFM) based retrieval system. SOM has good feature extracting property due to its topological ordering. The ear Analytics results for the 4 images of database reflect that the ear recognition using one of the neural network algorithms SOM for 4 persons. MATLAB programs were used to complete this work.
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spelling doaj.art-dfc0df4bf8cf4a60a6ae956e49b49c5a2024-02-04T17:36:03ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582013-07-0131102000201310.30684/etj.31.10A1482289Ear Recognition by Using Self Organizing Feature MapSuad K. MohammadA wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else.The aim of the work presented within this paper is to develop an optimum image compression system using haar wavelet transform and a neural network. In this paper we have developed and illustrated a recognition system for human ears using a Kohonen self-organizing map (SOM) or Self-Organizing Feature Map (SOFM) based retrieval system. SOM has good feature extracting property due to its topological ordering. The ear Analytics results for the 4 images of database reflect that the ear recognition using one of the neural network algorithms SOM for 4 persons. MATLAB programs were used to complete this work.https://etj.uotechnology.edu.iq/article_82289_be6ef8f293a9f61db6084b01013b9480.pdfimage compressiontwodimensional wavelet packet analysishaar waveletvector quantizationselforganizing feature mapneural network and pattern recognition
spellingShingle Suad K. Mohammad
Ear Recognition by Using Self Organizing Feature Map
Engineering and Technology Journal
image compression
two
dimensional wavelet packet analysis
haar wavelet
vector quantization
self
organizing feature map
neural network and pattern recognition
title Ear Recognition by Using Self Organizing Feature Map
title_full Ear Recognition by Using Self Organizing Feature Map
title_fullStr Ear Recognition by Using Self Organizing Feature Map
title_full_unstemmed Ear Recognition by Using Self Organizing Feature Map
title_short Ear Recognition by Using Self Organizing Feature Map
title_sort ear recognition by using self organizing feature map
topic image compression
two
dimensional wavelet packet analysis
haar wavelet
vector quantization
self
organizing feature map
neural network and pattern recognition
url https://etj.uotechnology.edu.iq/article_82289_be6ef8f293a9f61db6084b01013b9480.pdf
work_keys_str_mv AT suadkmohammad earrecognitionbyusingselforganizingfeaturemap