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Mining image frequent patterns based on a frequent pattern list in image databases

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Abstract

The goal of image mining is to find the useful information hidden in image databases. The 9DSPA-Miner approach uses the Apriori strategy to mine the image database, where each image is represented by the 9D-SPA representation. It presents a reasoning method to reason the unknown spatial relation that satisfies the spatial consistency. However, it may generate invalid candidates with the impossible relations that cannot be found in the 2D space or in the input database. Moreover, in this approach, counting the support of the pattern needs to intersect the associated image sets by searching the index structure, taking a long time. Therefore, in this paper, we propose an approach with a frequent pattern list, which generates all valid candidates of frequent patterns. Based on the frequent pattern list, the proposed approach presents two conditions in the candidate generation for finding frequent spatial patterns to avoid generating impossible candidates. Moreover, the proposed approach uses an additional verification step to further avoid generating impossible spatial relations. Therefore, the proposed approach generates fewer candidates than the 9DSPA-Miner approach, reducing the processing time. The experimental results have verified that the proposed approach outperforms the 9DSPA-Miner approach.

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Acknowledgements

This research was supported by Grant MOST 107-2221-E-110-064 from the Ministry of Science and Technology, Taiwan.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, 80424, Taiwan

    Ye-In Chang, Chia-En Li, Zih-Siang Chen & Ming-Hsuan Tu

  2. Department of Information Communication, Asia University, Taichung, 41354, Taiwan

    Jun-Hong Shen

  3. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40447, Taiwan

    Jun-Hong Shen

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  1. Ye-In Chang
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Correspondence to Jun-Hong Shen.

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Chang, YI., Shen, JH., Li, CE. et al. Mining image frequent patterns based on a frequent pattern list in image databases. J Supercomput 76, 2597–2621 (2020). https://doi.org/10.1007/s11227-019-03041-y

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