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Adaptive Color Independent Components Based SIFT Descriptors for Image Classification

机译:基于自适应颜色独立成分的SIFT描述符用于图像分类

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This paper proposes an adaptive color independent components based SIFT descriptor (termed CIC-SIFT) for image classification. Our motivation is to seek an adaptive and efficient color space for color SIFT feature extraction. Our work has two key contributions. First, based on independent component analysis (ICA), an adaptive and efficient color space is proposed for color image representation. Second, in this ICA-based color space, a discriminative CIC-SIFT descriptor is calculated for image classification. The experiment results indicate that (1) contrast between objects and background can be enhanced on the ICA-based color space and (2) the CIC-SIFT descriptor outperforms other conventional color SIFT descriptors on image classification.
机译:本文提出了一种基于色彩独立成分的自适应SIFT描述符(称为CIC-SIFT),用于图像分类。我们的动机是为彩色SIFT特征提取寻求一种自适应,高效的色彩空间。我们的工作有两个主要贡献。首先,基于独立分量分析(ICA),提出了一种自适应高效的色彩空间用于彩色图像表示。其次,在这种基于ICA的色彩空间中,计算出具有区别性的CIC-SIFT描述符以进行图像分类。实验结果表明:(1)在基于ICA的色彩空间上可以增强对象与背景之间的对比度;(2)CIC-SIFT描述符在图像分类方面优于其他常规的彩色SIFT描述符。

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