Abstract
Leaf venation is an important source of data for research in comparative plant biology. This paper presents a method for evolving classifiers capable of extracting the venation from leaf images. Quantitative and qualitative analysis of the classifier produced is carried out. The results show that the method is capable of the extraction of near complete primary and secondary venations with relatively little noise. For comparison, a method using ant colony algorithms is also discussed.
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Cope, J.S., Remagnino, P., Barman, S., Wilkin, P. (2010). The Extraction of Venation from Leaf Images by Evolved Vein Classifiers and Ant Colony Algorithms. In: Blanc-Talon, J., Bone, D., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2010. Lecture Notes in Computer Science, vol 6474. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17688-3_14
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DOI: https://doi.org/10.1007/978-3-642-17688-3_14
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