Circle Detection System Using Image Moments

Fachruddin, Rifqi; Buliali, Joko Lianto

doi:10.1109/cyberneticscom55287.2022.9865355

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…First of all, reducing candidate points [15] by, using multi-segmented line segments [16,17], and using the line segments on the arc to detect the circle were suggested. Second, the concepts of the isosceles triangle [18][19][20] and the right triangle [21] were also proposed as potential methods to detect the circle on the arc. However, the methods could not provide a better solution for being too complex and having invalid voting.…”

Section: Introductionmentioning

confidence: 99%

Nut Geometry Inspection Using Improved Hough Line and Circle Methods

Lin

Lien

2023

Sensors

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Nuts are the cornerstone of human industrial construction, especially A-grade nuts that can only be used in power plants, precision instruments, aircraft, and rockets. However, the traditional nuts inspection method is to manually operate the measuring instrument for conducting an inspection, so the quality of the A-grade nut cannot be guaranteed. In this work, a machine vision-based inspection system was proposed, which performs a real-time geometric inspection of the nuts before and after tapping on the production line. In order to automatically screen out A-Grade nuts on the production line, there are 7 inspections within this proposed nut inspection system. The measurements of parallel, opposite side length, straightness, radius, roundness, concentricity, and eccentricity were proposed. To shorten the overall detection time regarding nut production, the program needed to be accurate and uncomplicated. By modifying the Hough line and Hough circle, the algorithm became faster and more suitable for nut detection. The optimized Hough line and Hough circle can be used for all measures in the testing process.

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