Line-Segment Clustering Algorithm for Chemical Structure

Abstract

Chemical bond recognition is an important sub-task of chemical structure recognition.The single bonds,double bonds and triple bonds of the chemical structure are all composed of line segments,and it is easy to produce redundant data and interfe-rence data when the Hough transform is used for line segment detection.To this end,a clustering algorithm is proposed to cluster the line segments in chemical bonds detected by Hough transform,during which the redundant line segments can be merged dynamically.Specifically,based on the analysis of spatial relationship between the line segments,the relative similarity measure and interval similarity measure between line segments are defined.A clustering method based on the merging of line segments is carried out by using these two measures.Experimental results show that the proposed similarity measures can comprehensively des-cribe the similarity between line segments.The algorithm can obtain good clustering results,and accurately restore the true position of the line segments in the chemical bonds.It is therefore an effective method for chemical structure image preprocessing.

Keywords

• chemical structure recognition|hough transform|chemical bond|clustering of line segments