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A Computer Vision-Based Software for Calculating Automotive Wiring Harness Length

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With the rapid development of electrification and intelligence in the automotive industry, the structural complexity of wiring harnesses continues to increase. Traditional methods for measuring wiring harness length face challenges such as low accuracy and slow efficiency when dealing with curled and branched harnesses. To address these challenges, this paper presents the design and implementation of a computer vision-based software solution for accurately calculating automotive wiring harness lengths. The software utilizes a computer vision model to calibrate the start and end points of harness branches, and employs image preprocessing techniques (including binarization and denoising) to obtain clear images of the harness. A skeletonization algorithm is then applied to refine and extract the structural outline of the harness. Based on this, a Depth-First Search (DFS) algorithm is used to accurately calculate the length of each branch. Experimental results show that the software designed in this paper can accurately measure the length of each branch in a short period, with an average accuracy of 94.36%. This method provides effective technical support for intelligent inspection and automated production of automotive wiring harnesses, with significant application value and broad prospects.
Title: A Computer Vision-Based Software for Calculating Automotive Wiring Harness Length
Description:
With the rapid development of electrification and intelligence in the automotive industry, the structural complexity of wiring harnesses continues to increase.
Traditional methods for measuring wiring harness length face challenges such as low accuracy and slow efficiency when dealing with curled and branched harnesses.
To address these challenges, this paper presents the design and implementation of a computer vision-based software solution for accurately calculating automotive wiring harness lengths.
The software utilizes a computer vision model to calibrate the start and end points of harness branches, and employs image preprocessing techniques (including binarization and denoising) to obtain clear images of the harness.
A skeletonization algorithm is then applied to refine and extract the structural outline of the harness.
Based on this, a Depth-First Search (DFS) algorithm is used to accurately calculate the length of each branch.
Experimental results show that the software designed in this paper can accurately measure the length of each branch in a short period, with an average accuracy of 94.
36%.
This method provides effective technical support for intelligent inspection and automated production of automotive wiring harnesses, with significant application value and broad prospects.

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