Speed v. Accuracy for High Resolution Colour Texture Classification

A Monadjemi, BT Thomas, M Mirmehdi

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

Methods for extracting features and classifying textures in high resolution colour images are presented. The proposed features are directional texture features obtained from the convolution of the Walsh-Hadamard transform with different orientations of texture patches from high resolution images, as well as simple chromatic features that correspond to hue and saturation in the HLS colour space. We compare the performance of these new features against Gabor transform features combined with HLS and Lab colour space features. Multiple classifiers are employed to combine both textural and chromatic features for better classification performance. We demonstrate a considerable reduction in computational costs, whilst maintaining close accuracy.
Translated title of the contributionSpeed v. Accuracy for High Resolution Colour Texture Classification
Original languageEnglish
Title of host publicationUnknown
EditorsP. L. Rosin, D. Marshall
PublisherBMVA Press
Pages143 - 152
Number of pages9
ISBN (Print)1901725197
Publication statusPublished - Sep 2002

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the 13th British Machine Vision Conference, BMVC 2002

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