Boundary Detection Using Pointwise Crisp article c
2016-08-23
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Application background
For image segmentation, edge detection, etc.; have shown that contrary, WeRecent trends it, is possible to achieve excellent boundary detection results toVery local information and low-dimensional feature spaces. This is achieved usingThe use of a novel statistical framework based on Pointwise mutual throughInformation.Key Technology
Boundaries between semantically meaningful ob- DetectingIn visual scenes is an important component of many vision algo- jectsIn this paper we, propose a novel method for detecting such rithms.Based on a simple underlying principle: pixels belonging to boundariesSame object exhibit higher statistical dependencies than pixels be- theTo dierent objects. We show how to derive an anity measure longingOn this principle using pointwise mutual information and, we show basedThis measure is indeed a good predictor of whether or not two pixels thatOn the same object. Using this anity with spectral clumatlab
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