NDLI: Guided Classification using CCV and Wavelet Features for Greenery and Non-Greenery Images

Content Provider	IEEE Xplore Digital Library
Author	Balamurugan, P. Rajesh, R.
Copyright Year	2008
Description	Author affiliation: Sch. of Comput. Sci. & Eng., Bharathiar Univ., Coimbatore (Balamurugan, P.; Rajesh, R.)
Abstract	This paper focuses on finding the image features in both spatial and wavelet domain and applied that for greenery and non-greenery image classification. The spatial color feature called guided color coherence feature(GCCF) & guided distance feature in wavelet(GDFW) are calculated for the purpose of classification. The color coherence vector is constructed for all images and is used to find three GCCFs namely $Delta_{H},$ $Delta_{G}$ & $Delta_{I}$ . For finding guided distance feature in wavelet (GDFW), the input images are decomposed into 16 blocks using 2-dimensional discrete wavelet transform. Then wavelet image feature vector is formed by calculating mean and variance in each block. The difference between guide wavelet image and input wavelet image is named as guided distance feature in wavelet(GDFW) is calculated. Here one or more guide images are used for finding these guided features. These parameters are given in different combinations as input to the adaptive neuro fuzzy inference system(ANFIS). The performance of system is illustrated with a set of 600 images containing both greenery and non-greenery images.
Starting Page	163
Ending Page	168
File Size	238750
Page Count	6
File Format	PDF
ISBN	9781424428748
DOI	10.1109/ICCCYB.2008.4721398
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-11-27
Publisher Place	Slovakia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy sets Adaptive systems Wavelet domain Content based retrieval Image retrieval Neural networks Humans Coherence Discrete wavelet transforms Fuzzy systems
Content Type	Text
Resource Type	Article

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