A Texture and Curvature Bimodal Leaf Recognition Model for Identification of Costa Rican Plant Species
Erick Mata-Montero$^{1}$, Jose Carranza-Rojas$^{1}$
$^{1}$Costa Rica Institute of Technology. Cartago Costa Rica
email: emata@itcr.ac.cr, jcarranza@itcr.ac.cr

Schedule:Thu 22st@10:45, Room: D

In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap’s underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant.

BibTex

@InProceedings{CLEI-2015:144640,
	author 		= {Erick Mata-Montero and Jose Carranza-Rojas},
	title 		= {A Texture and Curvature Bimodal Leaf Recognition Model for Identification of Costa Rican Plant Species},
	booktitle 	= {2015 XLI Latin American Computing Conference (CLEI)},
	pages 		= {41--52},
	year 		= {2015},
	editor 		= {Hector Cancela and Alex Cuadros-Vargas and Ernesto Cuadros-Vargas},
	address 	= {Arequipa-Peru},
	month 		= {October},
	organization 	= {CLEI},
	publisher 	= {CLEI},
	url 		= {http://clei.org/clei2015/144640},
	isbn 		= {978-1-4673-9143-6},
	}