An Adaptive Algorithm for Workpiece Edge Detection Combining Morphology and Canny Operator

Yuan Li, Byung-Won Min, Ke Li

Article ID: 5509
Vol 7, Issue 4, 2024

VIEWS - 19 (Abstract) 9 (PDF)

Abstract


Addressing the challenges of limited noise suppression, inaccurate edge detection, and poor adaptability encountered in the detection of workpiece image edges in complex industrial environments, this study introduces an adaptive algorithm for edge detection that
integrates morphological processing with the Canny operator. Firstly, a weighted adaptive morphological processing is designed to extract the
gradient magnitude and direction. Secondly, this extracted information is weighted fused with the gradient magnitude and direction obtained
from the traditional Canny operator. Subsequently, an adaptive dual threshold algorithm is devised for edge detection and connection. Finally,
the proposed algorithm is experimentally validated using images collected from industrial robot assembly lines. The results demonstrate that
the proposed algorithm outperforms traditional methods, detecting more effective and continuous edges with significant noise reduction.

Keywords


Morphology; Canny Operator; Workpiece Edge Detection; Adaptive; Fusion Algorithm

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DOI: https://doi.org/10.18686/ijmss.v7i4.5509

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