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Image flower recognition based on a new method for color feature extraction

机译:基于一种新的颜色特征提取方法的图像花识别

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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.
机译:在本文中,我们首先介绍一种基于SURF检测器的颜色特征提取新方法。然后,我们证明了其在花卉图像分类中的有效性。因此,我们使用紧凑而准确的描述符描述了花朵图像的视觉内容。将这些功能组合在一起,并使用带有SVM分类器的多内核框架执行学习过程。该方法已经在牛津大学提供的数据集上进行了测试,并且在分类率和执行时间方面,比我们对Nilsback和Zisserman(Nilsback and Zisserman,2008)提出的方法的实施效果更好。

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