Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Digital Image Processing
General match: a subsequence matching method in time-series databases based on generalized windows
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Querying Time Series Data Based on Similarity
IEEE Transactions on Knowledge and Data Engineering
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Warping indexes with envelope transforms for query by humming
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A Generic Scheme for Color Image Retrieval Based on the Multivariate Wald-Wolfowitz Test
IEEE Transactions on Knowledge and Data Engineering
Rotation invariant indexing of shapes and line drawings
Proceedings of the 14th ACM international conference on Information and knowledge management
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A novel filtration method in biological sequence databases
Pattern Recognition Letters
Efficient moving average transform-based subsequence matching algorithms in time-series databases
Information Sciences: an International Journal
Ranked subsequence matching in time-series databases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Scaling-invariant boundary image matching using time-series matching techniques
Data & Knowledge Engineering
Publishing time-series data under preservation of privacy and distance orders
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
An envelope-based approach to rotation-invariant boundary image matching
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
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To achieve the noise reduction effect in boundary image matching, we exploit the moving average transformof time-series matching. Our motivation is that using the moving average transform we may reduce noise in boundary image matching as in time-series matching. We first propose a new notion of k-order image matching, which applies the moving average transform to boundary image matching. A boundary image can be represented as a sequence in the time-series domain, and our k-order image matching identifies similar boundary images in this time-series domain by comparing the k-moving average transformed sequences. Next, we propose an index-based method that efficiently performs k-order image matching on a large image database, and prove its correctness. Moreover, we present its index building and k-order image matching algorithms. Experimental results show that our k-order image matching exploits the noise reduction effect, and our index-based method outperforms the sequential scan by one or two orders of magnitude.