DocumentCode :
153036
Title :
Plant identification using local invariants
Author :
Yildiran, S. Tolga ; Yanikoglu, Benin ; Abdullah, Emran
Author_Institution :
Muhendislik ve Doga Bilimleri Fak., Sabanci Univ., Istanbul, Turkey
fYear :
2014
fDate :
23-25 April 2014
Firstpage :
2094
Lastpage :
2097
Abstract :
We present a plant image recognition system geared towards plants with flowers. The system uses local invariants with Dense SIFT features and Bag of Visual Words representation, while the classification is done using Support Vector Machines. Our approach contains a pre-classification stage where images are categorized into color subgroups, to reduce the complexity of the problem. Using a 161-class subset of the ImageClef´2013 flower dataset, the classification accuracy is measured as %42.68, compared to %18 eithout the pre-classification.
Keywords :
image classification; support vector machines; transforms; bag of visual words representation; dense SIFT feature; local invariant; plant identification; plant image recognition system; preclassification stage; scale invariant feature transform; support vector machines; Computer vision; Conferences; Histograms; Image color analysis; Signal processing; Support vector machines; Visualization; Bag of Visual Words (BOVW); Dense SIFT; K Means Clustering; PHOW; SVMs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2014 22nd
Conference_Location :
Trabzon
Type :
conf
DOI :
10.1109/SIU.2014.6830674
Filename :
6830674
Link To Document :
بازگشت