Abstract：
:Recent computational and psychological theories of human texture vision assert that texture discrimination is based on first-order differences in geometric and luminance attributes of texture elements, called 'textons'. Significant differences in the density, orientation, size, or contrast of line segments or other small features in an image have been shown to cause immediate perception of texture boundaries. However, the psychological theories, which are based on the perception of synthetic images composed of lines and symbols, neglect two important issues. First, how can textons be computed from grey-level images of natural scenes? And second, how, exactly, can texture boundaries be found? Our analysis of these two issues has led to an algorithm that is fully implemented and which successfully detects boundaries in natural images. We propose that blobs computed by a centre-surround operator are useful as texture elements, and that a simple non-parametric statistic can be used to compare local distributions of blob attributes to locate texture boundaries. Although designed for natural images, our computation agrees with some psychophysical findings, in particular, those of Adelson and Bergen (described in the preceding article), which cast doubt on the hypothesis that line segment crossings or termination points are textons.
journal_name
Naturejournal_title
Natureauthors
Voorhees H,Poggio Tdoi
10.1038/333364a0subject
Has Abstractpub_date
1988-05-26 00:00:00pages
364-7issue
6171eissn
0028-0836issn
1476-4687journal_volume
333pub_type
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