Title :
Morphological features for leaf based plant recognition
Author :
Aptoula, E. ; Yanikoglu, Benin
Author_Institution :
Comput. Eng. Dept., Okan Univ., Istanbul, Turkey
Abstract :
Although plant recognition has become an increasingly popular research topic, it remains nonetheless a scientific and technical challenge. Besides all the difficulties of classic object recognition, such as illumination, viewpoint and scale variations, plants can additionally exhibit visual changes depending on their age and condition, thus demanding a specialized approach. In this paper, we present two descriptors based on mathematical morphology; the first consists of the computation of morphological covariance on the leaf contour profile and the second is an extension of the recently introduced circular covariance histogram, capturing leaf venation characteristics. The effectiveness of both descriptors has been validated with the ImageClef´12 plant identification dataset.
Keywords :
biology computing; botany; covariance analysis; feature extraction; mathematical morphology; object recognition; ImageClef´12 plant identification dataset; circular covariance histogram; illumination variation; leaf based plant recognition; leaf contour profile; leaf venation characteristics; mathematical morphology; morphological covariance; morphological features; object recognition; plant age; plant condition; scale variation; viewpoint variation; Plant recognition; circular covariance histogram; feature extraction; mathematical morphology; morphological covariance;
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
DOI :
10.1109/ICIP.2013.6738307