A psychophysical evaluation of texture degradation descriptors

Jiri Filip, Pavel Vácha, Michal Haindl, Patrick R. Green

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


Delivering digitally a realistic appearance of materials is one of the most difficult tasks of computer vision. Accurate representation of surface texture can be obtained by means of view- and illumination-dependent textures. However, this kind of appearance representation produces massive datasets so their compression is inevitable. For optimal visual performance of compression methods, their parameters should be tuned to a specific material. We propose a set of statistical descriptors motivated by textural features, and psychophysically evaluate their performance on three subtle artificial degradations of textures appearance. We tested five types of descriptors on five different textures and combination of thirteen surface shapes and two illuminations. We found that descriptors based on a two-dimensional causal auto-regressive model, have the highest correlation with the psychophysical results, and so can be used for automatic detection of subtle changes in rendered textured surfaces in accordance with human vision. © 2010 Springer-Verlag Berlin Heidelberg.

Original languageEnglish
Title of host publicationStructural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, SSPR and SPR 2010, Proceedings
Number of pages11
Volume6218 LNCS
Publication statusPublished - 2010
Event7th Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition - Cesme, Izmir, Turkey
Duration: 18 Aug 201020 Aug 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6218 LNCS
ISSN (Print)0302-9743


Conference7th Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Abbreviated titleSSPR and SPR 2010
CityCesme, Izmir


  • BTF
  • degradation
  • eye-tracking
  • statistical features
  • texture
  • visual psychophysics


Dive into the research topics of 'A psychophysical evaluation of texture degradation descriptors'. Together they form a unique fingerprint.

Cite this