Abstract
Recognizing plant leaves has so far been an important and difficult task. This paper introduces a method of recognizing leaf images based on shape features using a hypersphere classifier. Firstly, we apply image segmentation to the leaf images. Then we extract eight geometric features including rectangularity, circularity, eccentricity, etc, and seven moment invariants for classification. Finally we propose using a moving center hypersphere classifier to address these shape features. As a result there are more than 20 classes of plant leaves successfully classified. The average correct recognition rate is up to 92.2 percent.
This work was supported by the NSF of China (Nos.60472111 and 60405002).
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Wang, XF., Du, JX., Zhang, GJ. (2005). Recognition of Leaf Images Based on Shape Features Using a Hypersphere Classifier. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_10
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DOI: https://doi.org/10.1007/11538059_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28226-6
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