Real two dimensional scaled matching

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

12 Scopus citations

Abstract

Scaled Matching refers to the problem of finding all locations in the text where the pattern, proportionally enlarged according to an arbitrary real-sized scale, appears. Scaled matching is an important problem that was originally inspired by Computer Vision. Finding a combinatorial definition that captures the concept of real scaling in discrete images has been a challenge in the pattern matching field. No definition existed that captured the concept of real scaling in discrete images, without assuming an underlying continuous signal, as done in the image processing field. We present a combinatorial definition for real scaled matching that scales images in a pleasing natural manner. We also present efficient algorithms for real scaled matching. The running time of our algorithm is as follows. If T is a two-dimensional n × n text array and P is a m × m pattern array, we find in T all occurrences of P scaled to any real value in time O(nm3 + n2m log m).

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsFrank Dehne, Jorg-Rudiger Sack, Michiel Smid
PublisherSpringer Verlag
Pages353-364
Number of pages12
ISBN (Print)3540405453
DOIs
StatePublished - 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2748
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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