Extensive research and development has taken place over the last 20 years in the areas of pattern recognition and image processing. Areas to which these disciplines have been applied include business (e. g., character recognition), medicine (diagnosis, abnormality detection), automation (robot vision), military intelligence, communications (data compression, speech recognition), and many others. This paper presents a very brief survey of recent developments in basic pattern recognition and image processing techniques.

Pattern Recognition and Image Processing

The many different mathematical techniques used to solve pattern recognition problems may be grouped into two general approaches [1,2]. They are the decision-theoretic (or discriminant) approach and the syntactic (or structural) approach [3]. In the decision-theoretic approach, a set of characteristic measurements, called features, are extracted from the patterns. Each pattern is represented by a feature vector, and the recognition of each pattern is usually made by partitioning the feature space. On the other hand, in the syntactic approach, each pattern is expressed as a composition of its components, called sub-patterns and pattern primitives. This approach draws an analogy between the structure of patterns and the syntax of a language. The recognition of each pattern is usually made by parsing the pattern structure according to a given set of syntax rules. In this paper, we briefly review the recent progress in syntactic pattern recognition and some of its applications.

Recent Advances in Syntactic Pattern Recognition

http://link.springer.com/content/pdf/10.1007/978-94-009-9941-1_1.pdf

Syntactic Pattern Recognition and its Applications to Signal Processing

Syntactic approach to pattern recognition is introduced. Special topics discussed include primitive selection and pattern grammars, syntactic recognition and error-correcting parsing, and clustering analysis for syntactic patterns.

Syntactic Approach to Pattern Recognition

http://link.springer.com/content/pdf/10.1007/978-94-009-9941-1_4.pdf

K. Hanakata

Papers

Feature Selection and Extraction for Decision Theoretic Approach and Structural Approach