Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 1-9.doi: 10.11896/jsjkx.201000044

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Recent Advances for Object Contour Detection Technology

FENG Fu-rong, ZHANG Zhao-gong   

  1. School of Computer Science and Technology,Heilongjiang University,Harbin 150080,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:FENG Fu-rong,born in 1986,postgra-duate.Her main research interests include object contour detection and object detection.
    ZHANG Zhao-gong,born in 1963,Ph.D,professor.His main research interests include bioinformatics,data mining,statistical genetics,big data,cloud computing etc.
  • Supported by:
    Natural Science Foundation of Heilongjiang Province,China(F2017024,F2017025).

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Abstract: Object contour detection is one of the most foundational,significant and challenging problems in the field of computer vision research.With the development of deep learning in recent years,breakthroughs have been made in other research directions in the field of vision,such as object detection and instance segmentation,which gradually prove the close relationship between contour detection and other research directions,so more and more attention has been paid in contour detection.This paper discusses several main contents,including not only a detailed review of the existing contour detection algorithms,but also three stages according to the features of contour detection and extraction:low-level,middle-level and high-level,and a detailed analysis of the applied datasets,performance evaluation indicators,model structure and model details,the application of contour detection and the application of its results,so as to make a deep understanding of the development of contour detection.Finally,the challenges and future trends of contour detection are analyzed and predicted.This paper provides new ideas and references for the follow-up research in this field.

Key words: Cluster, Computer vision, Contour detection, Deep learning, Segmentation

CLC Number: 

  • TP391
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