Pattern analysis using principle component analysis (PCA) method for herbs identification

Pattern analysis using principle component analysis (PCA) method for herbs identification

Herb is one of the plant species that each has unique odors. Each herb species has unique odor which differs from each other. This odor parameter is used to differentiate the type of herbs species based on response signals from E-Nose system. The response of electrical signal is generated when the g...

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Bibliographic Details
Main Authors: Mohamad Radzi, Nur Fadzilah, Che Soh, Azura, Mohamad Yusof, Umi Kalsom, Hassan, Mohd Khair, Khamis, Shamsul
Format: Conference or Workshop Item
Language:English
Published: Faculty of Computer Science and Information Technology, Universiti Putra Malaysia 2015
Online Access:http://psasir.upm.edu.my/id/eprint/65628/1/SAES2015%20-%20NFMR.pdf
Description
Summary:Herb is one of the plant species that each has unique odors. Each herb species has unique odor which differs from each other. This odor parameter is used to differentiate the type of herbs species based on response signals from E-Nose system. The response of electrical signal is generated when the gas sensor array detect the odor of herb species. This paper presents a pattern analysis of electrical signal data by using Principle Component Analysis (PCA) method. The different herb species with same group family were investigated. The result shows the discrimination between herb species is possible using the proposed method.

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