Extraction of discontinuous chains of symbols by means of perceptual grouping

Abstract

This paper proposes a new algorithm which applies perceptual grouping to track discontinuous chains of symbols in digitized maps. The procedure is based on an artificial intelligence kernel that supervises three different auxiliary processes: the search strategy generation module, responsible for the strategy to scan pixels; the symbol detection module that extracts the recognized symbols; the cost function evaluation module that assigns a global quality index to each symbol by considering the whole course of the line. Selected Gestalt rules are used to optimize the grouping procedures.