Abstract
Efficient algorithms exist for the approximate two dimensional matching problem for rectangles. This is the problem of finding all occurrences of an m × m pattern in an n × n text with no more than k mismatch, insertion, and deletion errors. In computer vision it is important to generalize this problem to non-rectangular figures. We make progress towards this goal by defining half-rectangular figures of height m and area a. The approximate two dimensional matching problem for half-rectangular patterns can be solved using a dynamic programming approach in time O(an2). We show an O(kn2√ m log m √ k log k + k2n2) algorithm which combines convolutions with dynamic programming. Note that our algorithm is superior to previous known solutions for k ≤ m1/3. At the heart of the algorithm are the Smaller Matching Problem and the k-Aligned Ones with Location Problem. These are interesting problems in their own right. Efficient algorithms to solve both these problems are presented.
Original language | English (US) |
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Pages (from-to) | 1-11 |
Number of pages | 11 |
Journal | Information and Computation |
Volume | 118 |
Issue number | 1 |
DOIs | |
State | Published - Apr 1995 |
ASJC Scopus subject areas
- Theoretical Computer Science
- Information Systems
- Computer Science Applications
- Computational Theory and Mathematics