Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (5): 113-119.doi: 10.11896/jsjkx.210700131

Special Issue: Big Data & Data Scinece

• Database & Big Data & Data Science • Previous Articles     Next Articles

Line-Segment Clustering Algorithm for Chemical Structure

ZHU Zhe-qing1,3, GENG Hai-jun1,3, QIAN Yu-hua1,2,3   

  1. 1 School of Computer and Information Technology,Shanxi University,Taiyuan 030006,China
    2 Key Laboratory Computational Intelligence and Chinese Information Processing of Ministry of Education,Shanxi University,Taiyuan 030006,China
    3 Institute of Big Data Science and Industry,Shanxi University,Taiyuan 030006,China
  • Received:2021-07-13 Revised:2021-12-10 Online:2022-05-15 Published:2022-05-06
  • About author:ZHU Zhe-qing,born in 1982,postgra-duate.His main research interests include machine learning and data mi-ning.
    QIAN Yu-hua,born in 1976,Ph.D,professor,is a member of China Computer Federation.His main reserch interests include pattern recognition,feature selection,rough set theory,granular computing and artifificial intelligence.
  • Supported by:
    National Natural Science Foundation of China(61672332),Key R & D Program of Shanxi Province (201903D421003),Science and Technology Achievements Transformation and Cultivation Project of Shanxi Provincial Education Department(2020CG001),Applied Basic Research Plan of Shanxi Province(20210302123444) and China University Industry-University-Research Innovation Fund(2021FNA02009).

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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.

Key words: Chemical bond, Chemical structure recognition, Clustering of line segments, Hough transform

CLC Number: 

  • TP391
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