Sub-Pixel Edge Detection Algorithm Based on Franklin Moments

To enhance the detection accuracy and computational efficiency of sub-pixel edge detection algorithms, this paper introduces a method based on Franklin moments. Constructed using the Franklin function system, these moments enable the simultaneous solution of matrix equations to determine sub-pixel model parameters and subsequently compute sub-pixel edge coordinates. The efficacy of the proposed approach is validated through experiments on both synthetic and real images. In tests involving synthetic circular images, the method demonstrates advantages in measuring circles of varying diameters with reduced computational time. Furthermore, in gauge diameter measurements, the approach achieves greater accuracy compared to the Zernike moment method.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/iaecst64597.2024.11117971
Primary Topic
Image Processing Techniques and Applications
Type
article
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article

Sub-Pixel Edge Detection Algorithm Based on Franklin Moments

Guanwei Wang, Wenmeng Chen, Huihui Tian, Hongxi Wang
Image Processing Techniques and Applications
article

Sub-Pixel Edge Detection Algorithm Based on Franklin Moments

Guanwei Wang, Wenmeng Chen, Huihui Tian, Hongxi Wang
article en

Abstract

To enhance the detection accuracy and computational efficiency of sub-pixel edge detection algorithms, this paper introduces a method based on Franklin moments. Constructed using the Franklin function system, these moments enable the simultaneous solution of matrix equations to determine sub-pixel model parameters and subsequently compute sub-pixel edge coordinates. The efficacy of the proposed approach is validated through experiments on both synthetic and real images. In tests involving synthetic circular images, the method demonstrates advantages in measuring circles of varying diameters with reduced computational time. Furthermore, in gauge diameter measurements, the approach achieves greater accuracy compared to the Zernike moment method.

Xi'an Technological University (CN)
Openalex Percentile: Top 56%
Image Processing Techniques and Applications
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