Authors:
Raffi Enficiaud
and
Sofiène Mouine
Affiliation:
INRIA Paris-Rocquencourt - IMEDIA, France
Keyword(s):
Plant identification, Venation extraction, Mathematical morphology, Computational botany.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Bioinformatics and Systems Biology
;
Computer Vision, Visualization and Computer Graphics
;
Data Engineering
;
Feature Selection and Extraction
;
Image Understanding
;
Information Retrieval
;
Object Recognition
;
Ontologies and the Semantic Web
;
Pattern Recognition
;
Software Engineering
;
Theory and Methods
Abstract:
The growing interest of Content Base Image Retrieval techniques in the context of plant identification requires
the development of appropriate features. A considerable amount of information about the taxonomic identity
of a plant is contained in its leaves, and most of the botanical expertise uses jointly the contour and the
venation network. The current work focuses principally on the extraction of the venation network, the base
and secondary landmarks of leaves with uncluttered background, assuming only their structure as palmate.
Morphological operators are used to extract a first approximation of the venation network, which is then
filtered by a voting scheme and reconstructed using a connected component like algorithm. The base point
and the primary veins are then extracted with an accuracy of 100%, which allows identification of the lobes
and the measurement their relative length.