Figure 16. Schematic diagram of industrial camera layout
3.2 Evaluation indicators for testing
results
In this paper, the average distance between the intersection coordinates
between the detection lines and the corresponding corner coordinates of
the suspender is used to evaluate the error size of the line detection
results, and determine whether the line detection results are within the
error range. Manually mark A, B, and C as the suspender corner points,
the intersection point between line and line is a, the intersection
point between line and is b, and the intersection point between line and
is c. Aa, Bb, and Cc are error distances between corresponding
coordinate points. Finally, the average error distance of Aa, Bb, and Cc
is used to measure the detection result. The schematic diagram of
evaluation criteria is shown in Figure 17:
Figure 17. Schematic Diagram of Evaluation Criteria
3.2 Analysis of results under different levels of
interference
This article lists four datasets with different interferences, and uses
the method proposed in this article and the original k-means clustering
method to detect four datasets. Each example includes an edge detection
graph, a Hough transform graph, the detection results of the two
algorithms, and a scatter plot of the straight line voting numbers of
the clustering results. To facilitate the display of the detection
effect, the detection image is now magnified by 10 times, and the test
example is shown in Figure 18.