The subset-matched Jaccard index for evaluation of Segmentation for Plant Images

We describe a new measure for the evaluation of region level segmentation of objects, as applied to evaluating the accuracy of leaf-level segmentation of plant images. The proposed approach enforces the rule that a region (e.g. a leaf) in either the image being evaluated or the ground truth image ev...

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Published inarXiv.org
Main Authors Bell, Jonathan, Dee, Hannah M
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 21.11.2016
Subjects
Ground truth
Image segmentation
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Abstract We describe a new measure for the evaluation of region level segmentation of objects, as applied to evaluating the accuracy of leaf-level segmentation of plant images. The proposed approach enforces the rule that a region (e.g. a leaf) in either the image being evaluated or the ground truth image evaluated against can be mapped to no more than one region in the other image. We call this measure the subset-matched Jaccard index.
AbstractList We describe a new measure for the evaluation of region level segmentation of objects, as applied to evaluating the accuracy of leaf-level segmentation of plant images. The proposed approach enforces the rule that a region (e.g. a leaf) in either the image being evaluated or the ground truth image evaluated against can be mapped to no more than one region in the other image. We call this measure the subset-matched Jaccard index.
Author Bell, Jonathan
Dee, Hannah M
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Title The subset-matched Jaccard index for evaluation of Segmentation for Plant Images
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