PLANT IDENTIFICATION USING LOCAL INVARIANTS
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Date
2014
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Ieee
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Abstract
We present a plant image recognition system geared towards plants with flowers. The system uses local invariants with Dense SIFT features and Bag of Visual Words representation, while the classification is done using Support Vector Machines. Our approach contains a pre-classification stage where images are categorized into color subgroups, to reduce the complexity of the problem. Using a 161-class subset of the ImageClef'2013 flower dataset, the classification accuracy is measured as %42.68, compared to %18 eithout the pre-classification.
Description
Yanikoglu, Berrin/0000-0001-7403-7592
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Keywords
Dense SIFT K Means Clustering, Bag of Visual Words (BOVW), SVMs, PHOW
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22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY
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Start Page
2094
End Page
2097