Pattern - Matching Problems for
نویسندگان
چکیده
The power of weighted nite automata to describe very complex images was widely studied, see [5, 6, 7]. Finite automata can be also used as an e ective tool for compression of twodimensional images. There are some software packages using this type of compression, see [12, 6]. We consider the complexity of some pattern-matching problems for two-dimensional images which are highly compressed using nite deterministic and weighted automata as small descriptions of images. Our main result is to show a dramatic growth of the time complexity when we pass from deterministic to weighted automata when solving our basic problem of compressed pattern-matching, where the pattern is given explicitely and the text is compressed. However, we show that deterministic automata can become quite complicated if we consider fully compressed pattern-matching (when also the pattern is compressed). We consider also fully compressed pattern-checking: testing of a given occurrence of the compressed pattern in a given position. We prove: Compressed matching for deterministic automata is in P. Compressed matching for weighted automata is NP-complete. Fully compressed pattern-checking for deterministic automata is in P. Fully compressed matching for deterministic automata is NP-complete. TUCS Research Group Mathematical Structures of Computer Science
منابع مشابه
6 D Classi cation of Pattern Matching Problems 1
We present our uni ed view to pattern matching problems and their solutions. We classify pattern matching problems by using six criteria and therefore we can locate them into six-dimensional space. We also show basic model of nondeterministic nite automaton that can be used for constructing models for all pattern matching problems.
متن کامل6d Classiication of Pattern Matching Problems 1
We present our uni ed view to pattern matching problems and their solutions. We classify pattern matching problems by using six criteria and therefore we can locate them into six-dimensional space. We also show basic model of nondeterministic nite automaton that can be used for constructing models for all pattern matching problems.
متن کاملLocal Derivative Pattern with Smart Thresholding: Local Composition Derivative Pattern for Palmprint Matching
Palmprint recognition is a new biometrics system based on physiological characteristics of the palmprint, which includes rich, stable, and unique features such as lines, points, and texture. Texture is one of the most important features extracted from low resolution images. In this paper, a new local descriptor, Local Composition Derivative Pattern (LCDP) is proposed to extract smartly stronger...
متن کاملRandomization in Parallel Stringology
In this abstract, we provide an overview of our survey of randomized techniques for exploiting the parallelism in string matching problems. Broadly, the study of string matching falls into two categories: standard stringology and nonstandard stringology. Standard Stringology concerns the study of various exact matching problems. The fundamental problem here is the basic string matching problem ...
متن کاملOn string matching with k mismatches
In this paper we consider several variants of the pattern matching problem. In particular, we investigate the following problems: 1) Pattern matching with k mismatches; 2) Approximate counting of mismatches; and 3) Pattern matching with mismatches. The distance metric used is the Hamming distance. We present some novel algorithms and techniques for solving these problems. Both deterministic and...
متن کامل