Abstract
Image retrieval plays an important role in the growing computer vision applications. The computation of the unrelated images in large scale image retrieval task seriously reduces the retrieval efficiency. In this paper, a new Partial Order Structure (POS) based image retrieval method is proposed. Partial order structure diagram is an effective visualization tool in Formal Concept Analysis (FCA) theory, including object partial order structure diagram and attribute partial order structure diagram. There are two contributions in this paper. First, we design an association rule according to the object partial order structure (OPOS) method to measure the correlation between the query image and the database, and then improve the database to be retrieved. Second, we perform a query expansion according to the attribute partial order structure (APOS) method to improve the generalization ability of the query information. Experimental results on two databases verify the effectiveness of the proposed algorithm.
The first author (Zhuoyi Li ) is a student.
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Acknowledgements
This work was partly supported by National Natural Science Foundation of China (No. 61303128), Natural Science Foundation of Hebei province (F2017203169), Key Scientific Research Projects of Colleges and Universities in Hebei province (ZD2017080), and Science and Technology Foundation for Returned Overseas People of Hebei Province (CL201621).
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Li, Z., Gu, G., Liu, J. (2019). Partial Order Structure Based Image Retrieval. In: Lin, Z., et al. Pattern Recognition and Computer Vision. PRCV 2019. Lecture Notes in Computer Science(), vol 11859. Springer, Cham. https://doi.org/10.1007/978-3-030-31726-3_11
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