A large number of growing digital images require retrieval effectively, but the trade-off between accuracy and speed is a tricky problem. This paperwork proposes a lightweight and efficient image retrieval approach by combining region and orientation correlation descriptors (CROCD). The region color correlation pattern and orientation color correlation pattern are extracted by the region descriptor and the orientation descriptor, respectively. The feature vector of the image is extracted from the two correlation patterns. The proposed algorithm has the advantages of statistic and texture description methods, and it can represent the spatial correlation of color and texture. The feature vector has only 80 dimensions for full color images specifically. Therefore, it is very efficient in image retrieving. The proposed algorithm is extensively tested on three datasets in terms of precision and recall. The experimental results demonstrate that the proposed algorithm outperforms other state-of-the-art algorithms.

中文翻译：

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基于区域和方向相关描述符组合的图像检索

大量不断增长的数字图像需要有效地检索，但是在准确性和速度之间进行权衡是一个棘手的问题。本文通过结合区域和方向相关描述符（CROCD）提出了一种轻巧有效的图像检索方法。区域颜色相关图案和取向颜色相关图案分别由区域描述符和取向描述符提取。从两个相关模式中提取图像的特征向量。该算法具有统计和纹理描述方法的优点，可以表示颜色和纹理的空间相关性。对于全彩色图像，特征向量只有80个维。因此，它在图像检索中非常有效。该算法在准确性和查全率方面在三个数据集上进行了广泛的测试。实验结果表明，所提出的算法优于其他最新算法。