NDLI: Feature Extraction Technique using Discrete Wavelet Transform for Image Classification

Content Provider	IEEE Xplore Digital Library
Author	Ghazali, K.H. Mansor, M.F. Mustafa, M.M. Hussain, A.
Copyright Year	2007
Description	Author affiliation: Univ. Malaysia, Kuantan (Ghazali, K.H.)
Abstract	The purpose of feature extraction technique in image processing is to represent the image in its compact and unique form of single values or matrix vector. Low level feature extraction involves automatic extraction of features from an image without doing any processing method. In this paper, we consider the use of high level feature extraction technique to investigate the characteristic of narrow and broad weed by implementing the 2 dimensional discrete wavelet transform (2D-DWT) as the processing method. Most transformation techniques produce coefficient values with the same size as the original image. Further processing of the coefficient values must be applied to extract the image feature vectors. In this paper, we propose an algorithm to implement feature extraction technique using the 2D-DWT and the extracted coefficients are used to represent the image for classification of narrow and broad weed. Results obtained suggest that the extracted 2D-DWT coefficients can uniquely represents the two different weed type.
Starting Page	1
Ending Page	4
File Size	3599295
Page Count	4
File Format	PDF
ISBN	9781424414697
DOI	10.1109/SCORED.2007.4451366
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-12
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image resolution Coefficient Image processing Weed Wavelet analysis Vectors Discrete wavelet transforms Wavelet coefficients Image analysis Feature extraction Spatial resolution Discrete Wavelet Transform Image classification
Content Type	Text
Resource Type	Article

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