Leaf Shape Recognition using Centroid Contour Distance

Workshop and International Seminar on Science of Complex Natural Systems

Hasim, Abdurrasyid^1 ; Herdiyeni, Yeni^1 ; Douady, Stephane^2

Department of Computer Science, Faculty of Mathematics and Natural Science, Bogor Agricultural University, West Java, Indonesia^1

Laboratoire : Matiere et System Complex, Université Paris Diderot, France^2

关键词: Boundary information;    High-accuracy;    Leaf images;    Leaf shape;    Probabilistic neural networks;    Shape descriptors;    Shape recognition;    Shape representation;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/31/1/012002/pdf
DOI  :  10.1088/1755-1315/31/1/012002

来源: IOP

【 摘 要 】

This research recognizes the leaf shape using Centroid Contour Distance (CCD) as shape descriptor. CCD is an algorithm of shape representation contour-based approach which only exploits boundary information. CCD calculates the distance between the midpoint and the points on the edge corresponding to interval angle. Leaf shapes that included in this study are ellips, cordate, ovate, and lanceolate. We analyzed 200 leaf images of tropical plant. Each class consists of 50 images. The best accuracy is obtained by 96.67%. We used Probabilistic Neural Network to classify the leaf shape. Experimental results demonstrated the effectiveness of the proposed approach for shape recognition with high accuracy.