Contour detection improved by context-adaptive surround suppression

Qiang Sang, Biao Cai and Hao Chen

PLOS ONE, 2017, vol. 12, issue 7, 1-13

Abstract: Recently, many image processing applications have taken advantage of a psychophysical and neurophysiological mechanism, called “surround suppression” to extract object contour from a natural scene. However, these traditional methods often adopt a single suppression model and a fixed input parameter called “inhibition level”, which needs to be manually specified. To overcome these drawbacks, we propose a novel model, called “context-adaptive surround suppression”, which can automatically control the effect of surround suppression according to image local contextual features measured by a surface estimator based on a local linear kernel. Moreover, a dynamic suppression method and its stopping mechanism are introduced to avoid manual intervention. The proposed algorithm is demonstrated and validated by a broad range of experimental results.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0181792

DOI: 10.1371/journal.pone.0181792

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