This paper presents a novel distance measure, the Minimum Landscape Distance (MLD). MLD is a warping distance measure that provides a non-linear mapping between the elements in one sequence to those of another. Each element in one sequence is mapped to that with the highest neighborhood structural similarity (landscape) in the other sequence within a window. Different window sizes are tested on a number of datasets and a linear relationship between the window size and the sequence size is discovered. Experimental results obtained on the Kimia-99 and Kimia-216 datasets show that MLD is superior to the Euclidean, correlation, and Dynamic Time Warping (DTW) distance measures. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Ebrahim, Y., Ahmed, M., Chau, S. C., & Abdelsalam, W. (2008). Shape matching using a novel warping distance measure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5112 LNCS, pp. 465–474). https://doi.org/10.1007/978-3-540-69812-8_46
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