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In this work, we propose a Triangle based approach to classify flower images.Initially, flowers are segmented using whorl based region merging segmentation.Skeleton of a flower is obtained from the segmented flower using a skeletonpruning method. The Delaunay triangulation is obtained from the endpoints andjunction points detected on the skeleton. The length and angle features areextracted from the obtained Delaunay triangles and then are aggregated torepresent in the form of interval-valued type data. A suitable classifier hasbeen explored for the purpose of classification. To corroborate the efficacy ofthe proposed method, an experiment is conducted on our own data set of 30classes of flowers, containing 3000 samples.

Delaunay Triangulation on Skeleton of Flowers for Classification