Title :
Image flower recognition based on a new method for color feature extraction
Author :
Amira Ben Mabrouk;Asma Najjar;Ezzeddine Zagrouba
Author_Institution :
Team of Research SIIVA- Lab. RIADI, Institut Supé
Abstract :
In this paper, we present, first, a new method for color feature extraction based on SURF detectors. Then, we proved its efficiency for flower image classification. Therefore, we described visual content of the flower images using compact and accurate descriptors. These features are combined and the learning process is performed using a multiple kernel framework with a SVM classifier. The proposed method has been tested on the dataset provided by the university of oxford and achieved better results than our implementation of the method proposed by Nilsback and Zisserman (Nilsback and Zisserman, 2008) in terms of classification rate and execution time.
Keywords :
"Image color analysis","Feature extraction","Visualization","Vocabulary","Shape","Support vector machines","Kernel"
Conference_Titel :
Computer Vision Theory and Applications (VISAPP), 2014 International Conference on