Image Flower Recognition based on a New Method for Color Feature Extraction

被引:0
|
作者
Ben Mabrouk, Amira [1 ]
Najjar, Asma [1 ]
Zagrouba, Ezzeddine [1 ]
机构
[1] Univ Tunis Elmanar, Inst Super Informat, Team Res SIIVA Lab RIADI, Tunis, Tunisia
关键词
SURF; Lab Color Space; Visual Vocabulary; SVM; MKL;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:201 / 206
页数:6
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