Abstract
In this paper, we present a novel feature extraction approach for plant leaf image recognition, which applies the arc length information to replace the Euclidean distance in traditional Shape Context (SC) method. Meanwhile, the shape is divided by the arc length into two parts, i.e. local and global feature. It can obtain the weighed cost of shape matching by combining the local with global feature. We compare this algorithm with the classic Inner-Distance Shape Context (IDSC) method on both Swedish and ICL leaf image dataset. Experimental results show that the proposed method achieves better performance compared with SC and IDSC methods.
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© 2012 Springer-Verlag Berlin Heidelberg
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Zhi, ZD., Hu, RX., Wang, XF. (2012). A New Weighted ARC-SC Approach for Leaf Image Recognition. In: Huang, DS., Ma, J., Jo, KH., Gromiha, M.M. (eds) Intelligent Computing Theories and Applications. ICIC 2012. Lecture Notes in Computer Science(), vol 7390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31576-3_64
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DOI: https://doi.org/10.1007/978-3-642-31576-3_64
Publisher Name: Springer, Berlin, Heidelberg
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