A New Model of Array Grammar for generating Connected Patterns on an Image Neighborhood

TL;DR

This paper introduces a new array grammar model that efficiently generates and recognizes connected patterns in image neighborhoods, aiding image analysis and pattern recognition tasks.

Contribution

The paper proposes a novel array grammar model capable of generating and deriving connected patterns in image neighborhoods, enhancing pattern recognition methods.

Findings

The new grammar can generate all simple and complex connected patterns.

It provides a systematic way to recognize connected patterns in small image neighborhoods.

The model improves the representation of connected patterns in image analysis.

Abstract

Study of patterns on images is recognized as an important step in characterization and classification of image. The ability to efficiently analyze and describe image patterns is thus of fundamental importance. The study of syntactic methods of describing pictures has been of interest for researchers. Array Grammars can be used to represent and recognize connected patterns. In any image the patterns are recognized using connected patterns. It is very difficult to represent all connected patterns (CP) even on a small 3 x 3 neighborhood in a pictorial way. The present paper proposes the model of array grammar capable of generating any kind of simple or complex pattern and derivation of connected pattern in an image neighborhood using the proposed grammar is discussed.