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Title of Journal: Multimed Tools Appl

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Abbravation: Multimedia Tools and Applications

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Springer US

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DOI

10.1002/ange.201302775

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1573-7721

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Spectral segmentation via minimum barrier distance

Authors: Jing Mao Zhang Yan Xia Shen
Publish Date: 2017/02/20
Volume: 76, Issue: 24, Pages: 25713-25729
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Abstract

Constructing a reliable affinity matrix is crucial for spectral segmentation In this paper we define a technique to create a reliable affinity matrix for the application to spectral segmentation We propose an affinity model based on the minimum barrier distance MBD First the image is oversegmented into superpixels then the subset of the pixels located in the center of these superpixels is used to compute the MBDbased affinities of the original image with particular care taken to avoid a strong boundary as described in the classical model To deal with images with faint object and random or “clutter” background we present gradient data that are integrated with the MBD data To capture different perceptual grouping cues the completed affinity model includes MBD color and spatial cues of the image Finally spectral segmentation is implemented at the superpixel level to provide an image segmentation result with pixel granularity Experiments using the Berkeley image segmentation database validate the effectiveness of the proposed method Covering PRI VOI and the Fmeasure are used to evaluate the results relative to several stateoftheart algorithms

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