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Color Object Retrieval Using Local Features Based on Opponent-Process Theory

机译:基于对手过程理论的本地特征,颜色对象检索

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Although the color is perceived as an irreplaceable element describing the world around us, the techniques for extracting of the local features are mostly based on the description of the intensities - while the color information is being fully ignored. This paper proposes a method for extracting of the local features of the color image. As a basic model we have chosen the approach to the human visual system using chromatic opponent channels and the SIFT (Scalable Invariant Feature Transform) method. The idea of this solution is the incorporation of the opponent chromatic channels by replacing the grayscale information in the SIFT method, so that the key points are detected on two separate opponent channels. For the interesting points found in the two channels, the descriptors are formed which are then united into one set. We also propose the new methods for the validation of the keypoint pairing utilizing the keypoint orientation consistency check. The algorithm was tested in an object retrieval experiment.
机译:尽管将颜色被认为是描述我们周围世界的不可替代的元件,但是用于提取局部特征的技术主要基于强度的描述 - 虽然颜色信息完全忽略。本文提出了一种用于提取彩色图像的局部特征的方法。作为一种基本模型,我们选择了使用色差通道和SIFT(可扩展不变特征变换)方法的人类视觉系统的方法。该解决方案的思想是通过在SIFT方法中替换灰度信息来结合对手的色信,从而在两个单独的对手通道上检测到关键点。对于两个通道中发现的有趣点,形成描述符,然后将其联合到一个集合。我们还提出了利用KeyPoint方向一致性检查验证关键点配对的新方法。该算法在对象检索实验中进行了测试。

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