Email this article Performance analysis of hybrid features derived from discrete wavelet transform based XCSLDP and first-order features for image retrieval
Abstract
In this work a simple and efficient discrete wavelet transform (DWT) based hybrid texture feature, fusing XCSLDP and first-order features texture descriptor is proposed to accurately classify the images. Primarily, DWT decomposes each image up to 3 levels using selected Daubechies (db3) wavelet as a decomposition filter. Subsequently, XCSLDP and four FOS features, namely, mean, standard deviation, skewness and kurtosis are employed to obtain substantial signatures of these images at different levels. The dwt based XCSLDP and FOS texture hybrid features, names as WXCSLDPFF, has achieved 74.68% ,86.7%, 91.33% and 75.12% on Corel1k, BrodatZ, MITVisTex and STex datasets respectively.
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