A New Model of Array Grammar for generating Connected Patterns on an Image Neighborhood
This work addresses a fundamental challenge in image analysis for researchers in syntactic methods, but it appears incremental as it builds on existing array grammar approaches without clear evidence of broad impact.
The paper tackles the problem of representing and recognizing connected patterns in images by proposing a new array grammar model that can generate any simple or complex pattern, with a focus on deriving these patterns in a 3x3 image neighborhood.
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.