Rangachari Anand, Kishan Mehrotra, et al.
IEEE Transactions on Neural Networks
Any notion of "closeness" in pattern matching should have the property that if A is close to B, and B is close to C, then A is close to C. Traditionally, this property is attained because of the triangle inequality (d(A, C) ≤ d(A, B) + d(B, C), where d represents a notion of distance). However, the full power of the triangle inequality is not needed for this property to hold. Instead, a "relaxed triangle inequality" suffices, of the form d(A, C) < c(d(A, B) + d(B, C)), where c is a constant that is not too large. In this paper, we show that one of the measures used for distances between shapes in (an experimental version of) IBM's QBIC1 ("Query by Image Content") system (Niblack et al., 1993) satisfies a relaxed triangle inequality, although it does not satisfy the triangle inequality.
Rangachari Anand, Kishan Mehrotra, et al.
IEEE Transactions on Neural Networks
Gang Liu, Michael Sun, et al.
ICLR 2025
George Saon
SLT 2014
Jehanzeb Mirza, Leonid Karlinsky, et al.
NeurIPS 2023