Extracting visual features for image retrieval by mimicking human cognition remains a challenge. Opponent color and HSV color spaces can mimic human visual perception well. In this paper, we improve and extend the CDH method using a multi-stage model to extract and represent an image in a way that mimics human perception. Our main contributions are as follows: (1) a visual feature descriptor is proposed to represent an image. It has the advantages of a histogram-based method and is consistent with visual perception factors such as spatial layout, intensity, edge orientation, and the opponent colors. (2) We improve the distance formula of CDHs; it can effectively adjust the similarity between images according to two parameters. The proposed method provides efficient performance in similar image retrieval rather than instance retrieval. Experiments with four benchmark datasets demonstrate that the proposed method can describe color, texture, and spatial features and performs significantly better than the color volume histogram, color difference histogram, local binary pattern histogram, and multi-texton histogram, and some SURF-based approaches.

中文翻译：

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使用融合感知色直方图的图像检索

通过模仿人类认知来提取视觉特征以进行图像检索仍然是一个挑战。对手颜色和HSV颜色空间可以很好地模仿人类的视觉感知。在本文中，我们使用多阶段模型改进和扩展了CDH方法，以模仿人类感知的方式提取和表示图像。我们的主要贡献如下：（1）提出了视觉特征描述符来表示图像。它具有基于直方图的方法的优点，并且与视觉感知因素（如空间布局，强度，边缘方向和对手的颜色）一致。（2）完善了CDH的距离公式；它可以根据两个参数有效地调整图像之间的相似度。所提出的方法在类似的图像检索而不是实例检索中提供了有效的性能。