Sabanci-Okan system at ImageClef 2012: combining features and classifiers for plant identification

Yanıkoğlu, Berrin and Aptoula, Erchan and Tırkaz, Çağlar (2012) Sabanci-Okan system at ImageClef 2012: combining features and classifiers for plant identification. In: Cross Language Evaluation Platform (CLEF), Rome, Italy

Full text not available from this repository. (Request a copy)

Abstract

We describe our participation in the plant identication task of ImageClef 2012. We submitted two runs, one fully automatic and another one where human assistance was provided for the images in the photo category. We have not used the meta-data in either one of the systems, for exploring the extent of image analysis for the plant identication problem. Our approach in both runs employs a variety of shape, texture and color descriptors (117 in total). We have found shape to be very discriminative for isolated leaves (scan and pseudoscan categories), followed by texture. While we have experimented with color, we could not make use of the color information. We have employed the watershed algorithm for segmentation, in slightly dierent forms for automatic and human assisted systems. Our systems have obtained the best overall results in both automatic and manual categories, with 43% and 45% identication accuracies respectively. We have also obtained the best results on the scanned image category with 58% accuracy.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: Plant identication, mathematical morphology, classier combination, support vector machines
Subjects: Q Science > QA Mathematics > QA075 Electronic computers. Computer science
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Berrin Yanıkoğlu
Date Deposited: 28 Nov 2012 16:25
Last Modified: 26 Apr 2022 09:07
URI: https://research.sabanciuniv.edu/id/eprint/20058

Actions (login required)

View Item
View Item