Boundary Detection in Digital Images using Structural Forests Method Based on Contour Grouping and Reasoning

Document Type : Persian Original Article

Authors

Department of Communication Engineering, University of Sistan and Baluchestan, University Street, Zahedan, Iran.

Abstract

Abstract- Edge detection is carried out using high-quality and real-time structural forests method. Nevertheless, in the output of this method, edges with a width of more than one pixel as well as unreal edges that do not belong to any boundary can be seen. Applying thresholds to this output cannot also eliminate all of these disadvantages and sometimes leads to the removal of edge pixels resulting in a loss of performance. In this paper, by presenting the extended structural forests method based on contour grouping and reasoning, while eliminating the disadvantages of the basic structural forests edge detector and improving its performance, a precise and high-quality boundary detector is achieved. By using this method and according to the F-measure criterion, the performance of edge detection is improved 2.26% in total. The proposed algorithm can be used as an effective preprocessing stage in many image processing functions by providing accurate boundaries with a width of one pixel.

Keywords

References

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Journal of Soft Computing and Information Technology
Volume 9, Issue 2 - Serial Number 28
Summer
July 2020
Pages 124-139

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