Application of Fuzzy Languages to Pattern Recognition

Abstract

The concept of a fuzzy language is applied to pattern recognition using geometric figures, chromosomes and leukocytes as illustrative examples. For chromosomes, an algorithm for classifying a chromosome image as an “approximate median chromosome,” “approximate sub‐median chromosome” or “approximate acrocentric chromosome” is presented. For leukocytes, an equal‐perimeter circular shape measure and an equal‐area circular shape measure are proposed, and various properties, results, and the relationship between these two measures are presented. Quantitative measures of other visual concepts such as elongated, spiculed, indented, slightly indented and deeply indented arc also presented and illustrated by examples. The results obtained in this paper may have useful applications in pattern recognition, cybernetics and fuzzy systems.

Research topics in pictorial databases

“…An alternative coding method for color pictures based on pattern recognition techniques (Lee, 1977, 1980a, 1982a, b; Lee and Zadeh, 1969) is investigated. In this approach, color clusters, color codebooks, an unsupervised learning algorithm, and a nearest‐neighbor classifier are thoroughly studied (Wu, 1986).…”

Fuzzy automata and languages: theory and applications

“…They give a very good account of more than 30 years writings on fuzzy and classical automata, fuzzy and classical languages and related fundamental contributions to applications. It should be better to include also comments on categorical aspects [1,5] and to mention the bibliography [1], as well as the books [6,8] and the papers [3,4]. This is a very profound book.…”

(1,7,4) Data hiding scheme for searching in hidden text with automata

“…Some of them can be seen in [15] for finite automata and [16][17][18] for fuzzy automata and fuzzy languages. In pattern matching problem, there are well-known algorithms: KMP and BM, where for given pattern text P and tagged text S, one reads the text S from left to right to verify and calculate the time that P is appeared in S. In KMP one, each letter S[i] of S is read in each step, i = 1, .…”

“…The hiding scheme (2,14,8) provides us a suited way to build an algorithm for searching hidden text by automata technique which now exists in several sources [15][16][17][18]. In this scheme, we introduce a fuzzy approach to searching hidden text by automata and introduce a hidden text searching technique in stego-images without revealing extracted text using our hiding scheme (2,14,8).…”

“…Data hiding [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] is interested in several authors because data hiding can be used for copyright, secret communication, military fields, and hospital, etc. Data hiding is referred to as a process to hide data (representing some information) into cover media.…”