CableDex: Cable Length Estimation on Industrial Reels Using a Handheld Device
2026-08-10 • Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition
AI summaryⓘ
The authors created CableDex, a system that can measure how long a cable is on a reel by analyzing just one photo taken with a phone. Instead of measuring cables by hand, which can be slow and wrong, their system uses advanced image techniques to identify the cable and figure out its length. They tested it on different types of reels and cables, and it was pretty accurate, making errors less than 5%. They also built a mobile app that guides users through the whole process, from scanning the reel to getting the cable length.
instance segmentationcamera calibrationpose estimationvolumetric calculationmean average precision (mAP)mean absolute percentage error (MAPE)mobile applicationcomputer visionindustrial cable measurementimage inference time
Authors
Francisco Guillén, Ricardo Almeida, Bruno Silva, João C. Neves
Abstract
CableDex is a computer vision system that addresses the time-consuming and inaccurate manual measurement of cable length on industrial reels from a single photograph captured with a mobile phone. The system combines camera calibration, instance segmentation, pose estimation, and volumetric calculation to estimate the cable length across five different reel types and various cable sizes. This system is based on an instance segmentation model trained on 1,000 manually annotated images, achieving 99.5\% mAP50 with an inference time of 5.66 ms per image. Evaluated on 75 reels across five reel types, the system achieves a MAPE of 4.90\%, within the 10\% error tolerance commonly accepted in industrial cable-reel measurement. The demonstration presents the end-to-end pipeline, from reel label scanning and image capture to segmentation and length estimation, through the mobile application.