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In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition, the match usually has to be exact: "either it will or will not be a match." The patterns generally have the form of either sequences or tree structures.
Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [ 2 ] navigation of mobile robots , [ 3 ] or edge detection in images.
Pattern recognition can be thought of in two different ways. The first concerns template matching and the second concerns feature detection. A template is a pattern used to produce items of the same proportions. The template-matching hypothesis suggests that incoming stimuli are compared with templates in the long-term memory.
String matching algorithms (1 C, 16 P) Pages in category "Pattern matching" The following 28 pages are in this category, out of 28 total.
A string-searching algorithm, sometimes called string-matching algorithm, is an algorithm that searches a body of text for portions that match by pattern. A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet ( finite set ) Σ.
In computer science, the Krauss wildcard-matching algorithm is a pattern matching algorithm. Based on the wildcard syntax in common use, e.g. in the Microsoft Windows command-line interface, the algorithm provides a non-recursive mechanism for matching patterns in software applications, based on syntax simpler than that typically offered by regular expressions.
The Rete algorithm (/ ˈ r iː t iː / REE-tee, / ˈ r eɪ t iː / RAY-tee, rarely / ˈ r iː t / REET, / r ɛ ˈ t eɪ / reh-TAY) is a pattern matching algorithm for implementing rule-based systems. The algorithm was developed to efficiently apply many rules or patterns to many objects, or facts , in a knowledge base .
Elastic matching is one of the pattern recognition techniques in computer science. Elastic matching (EM) is also known as deformable template, flexible matching, or nonlinear template matching. [1] Elastic matching can be defined as an optimization problem of two-dimensional warping specifying corresponding pixels between subjected images.