Paper
27 August 1992 Identifying high-level features of texture perception
A. Ravishankar Rao, Gerald L. Lohse
Author Affiliations +
Proceedings Volume 1666, Human Vision, Visual Processing, and Digital Display III; (1992) https://doi.org/10.1117/12.135988
Event: SPIE/IS&T 1992 Symposium on Electronic Imaging: Science and Technology, 1992, San Jose, CA, United States
Abstract
A fundamental issue in texture analysis is that of deciding what textural features are important in texture perception, and how they are used. Experiments on human pre-attentive vision have identified several low-level features (such as orientation on blobs, and size of line segments), which are used in texture perception. However, the question of what higher level features of texture are used has not been adequately addressed. We designed an experiment to help identify the relevant higher order features of texture perceived by humans. We used twenty subjects, who were asked to perform an unsupervised classification of thirty pictures from Brodatz's album on texture. Each subject was asked to group these pictures into as many classes as desired. Both hierarchical cluster analysis and non-metric MDS were applied to the pooled similarity matrix generated from the subjects' groupings. A surprising outcome is that the MDS solutions fit the data very well. The stress in the two dimensional case is 0.10, and in the three dimensional case is 0.045. We rendered the original textures in these coordinate systems, and interpreted the (rotated) axes. It appears that the axes in the 2D case correspond to periodicity versus irregularity, and directional versus non-directional. In the 3D case, the third dimension represents the structural complexity of the texture. Furthermore, the clusters identified by the hierarchical cluster analysis remain virtually intact in the MDS solution. The results of our experiment indicate that people use three high level features for texture perception. Future studies are needed to determine the appropriateness of these high-level features for computational texture analysis and classification.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Ravishankar Rao and Gerald L. Lohse "Identifying high-level features of texture perception", Proc. SPIE 1666, Human Vision, Visual Processing, and Digital Display III, (27 August 1992); https://doi.org/10.1117/12.135988
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Cited by 8 scholarly publications.
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KEYWORDS
Visualization

Human vision and color perception

Image classification

Analytical research

Computer vision technology

Machine vision

Taxonomy

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