TY - GEN
T1 - A venation-based leaf image classification scheme
AU - Park, Jin Kyu
AU - Hwang, Een Jun
AU - Nam, Yunyoung
PY - 2006
Y1 - 2006
N2 - Most content-based image retrieval systems use image features such as textures, colors, and shapes. However, in the case of leaf image, it is not appropriate to rely on color or texture features only because such features are similar in most leaves. In this paper, we propose a novel leaf image retrieval scheme which first analyzes leaf venation for leaf categorization and then extracts and utilizes shape feature to find similar ones from the categorized group in the database. The venation of a leaf corresponds to the blood vessel of organisms. Leaf venations are represented using points selected by the curvature scale scope corner detection method on the venation image, and categorized by calculating the density of feature points using non-parametric estimation density. We show its effectiveness by performing several experiments on the prototype system.
AB - Most content-based image retrieval systems use image features such as textures, colors, and shapes. However, in the case of leaf image, it is not appropriate to rely on color or texture features only because such features are similar in most leaves. In this paper, we propose a novel leaf image retrieval scheme which first analyzes leaf venation for leaf categorization and then extracts and utilizes shape feature to find similar ones from the categorized group in the database. The venation of a leaf corresponds to the blood vessel of organisms. Leaf venations are represented using points selected by the curvature scale scope corner detection method on the venation image, and categorized by calculating the density of feature points using non-parametric estimation density. We show its effectiveness by performing several experiments on the prototype system.
UR - http://www.scopus.com/inward/record.url?scp=33751369834&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33751369834&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33751369834
SN - 3540457801
SN - 9783540457800
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 416
EP - 428
BT - Information Retrieval Technology - Third Asia Information Retrieval Symposium, AIRS 2006, Proceedings
PB - Springer Verlag
T2 - 3rd Asia Information Retrieval Symposium, AIRS 2006
Y2 - 16 October 2006 through 18 October 2006
ER -