This paper proposes an indexing technique for fast retrieval of similar image subsequences using the multi-dimensional time warping distance. The time warping distance is a more suitable similarity measure as compared to the Lp distance in many applications where sequences may be of different lengths and/or different sampling rates. Our indexing scheme employs a disk-based suffix tree as an index structure and uses a lower-bound distance function to filter out dissimilar subsequence without false dismissals. It applies the normalization for an easier control of relative weighting of feature dimensions and the discretization to compress the index tree. Experiments on medical and synthetic image sequences verified that the proposed method significantly outperforms the naïve method and scales well in a large volume of image sequence databases.
Bibliographical noteFunding Information:
∗This research is supported in part by NIC/NIH Grant #442511-33780.
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Computer Graphics and Computer-Aided Design