Delving into the whorl of flower segmentation | Zendy

M.-E. Nilsback | Zendy; Andrew Zisserman | Zendy

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Delving into the whorl of flower segmentation

Author(s) -

M.-E. Nilsback,

Andrew Zisserman

Publication year - 2007

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5244/c.21.54

Subject(s) - whorl (mollusc) , segmentation , petal , ground truth , artificial intelligence , computer science , image segmentation , computer vision , variation (astronomy) , pattern recognition (psychology) , market segmentation , graph , function (biology) , variety (cybernetics) , biology , botany , evolutionary biology , theoretical computer science , genus , physics , marketing , astrophysics , business

We describe an algorithm for automatically segmenting flowers in colour photographs. This is a challenging problem because of the sheer variety of flower classes, the intra-class variability, the variation within a particular flower, and the variability of imaging conditions ‐ lighting, pose, foreshortening etc. The method couples two models ‐ a colour model for foreground and background, and a generic shape model for the petal structure. This shape model is tolerant to viewpoint changes and petal deformations, and applicable across many different flower classes. The segmentations are produced using a MRF cost function optimized using graph cuts. The algorithm is tested on 13 flower classes and more than 750 examples. Performance is assessed against ground truth segmentations.

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