Abstract
In this paper, a multiple classification method for plant species based on Gabor filters and local binary patterns (LBP) operator is proposed. We classify plant species by extracting global texture features with Gabor filters and local features with LBP operator. Simply speaking, the LBP operator is conducted on the magnitude maps of multi-scale and multi-orientation Gabor filtered image rather than original image. Thus, a plant leaf is presented as more spatial histograms with varying scales and orientations. The method has impressively improved the performance comparing with using Gabor transform or LBP absolutely.
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© 2008 Springer-Verlag Berlin Heidelberg
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Lin, FY., Zheng, CH., Wang, XF., Man, QK. (2008). Multiple Classification of Plant Leaves Based on Gabor Transform and LBP Operator. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2008. Communications in Computer and Information Science, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85930-7_55
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DOI: https://doi.org/10.1007/978-3-540-85930-7_55
Publisher Name: Springer, Berlin, Heidelberg
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