Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.756237
Title: Quantifying texture scale in accordance with human perception
Author: Bouremoum, Sami
ISNI:       0000 0004 7429 1904
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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Abstract:
Visual texture has multiple perceptual attributes (e.g. regularity, isotropy, etc.), including scale. The scale of visual texture has been defined as the size of the repeating unit (or texel) of which the texture is composed. Not all textures are formed through the placement of a clearly discernible repeating unit (e.g. irregular and stochastic textures). There is currently no rigorous definition for texture scale that is applicable to textures of a wide range of regularities. We hypothesised that texture scale ought to extend to these less regular textures. Non-overlapping sample windows (or patches) taken from a texture appear increasingly similar as the size of the window gets larger. This is true irrespective of whether the texture is formed by the placement of a discernible repeating unit or not. We propose the following new characterisation for texture scale: “the smallest window size beyond within which texture appears consistently”. We perform two psychophysical studies and report data that demonstrates consensus across subjects and across methods of probing in the assessment of texture scale. We then present an empirical algorithm for the estimation of scale based on this characterisation. We demonstrate agreement between the algorithm and (subjective) human assessment with an RMS accuracy of 1.2 just-noticeable-differences, a significant improvement over previous published algorithms. We provide two ground-truth perceptual datasets, one for each of our psychophysical studies, for the texture scale of the entire Brodatz album, together with confidence levels for each of our estimates. Finally, we make available an online tool which researchers can use to obtain texture scale estimates by uploading images of textures.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.756237  DOI: Not available
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