Benchmarks for Industrial Inspection Based on Structured Light
Robustness and accuracy are two critical metrics for industrial inspection. In this paper, we propose benchmarks that can evaluate the structured light method's performance. Our evaluation metric was learning from a lot of inspection tasks from the factories. The metric we proposed consists of four detailed criteria such as flatness, length, height and sphericity. Then we can judge whether the structured light method/device can be applied to a specified inspection task by our evaluation metric quickly. A structured light device built for TypeC pin needles inspection performance is evaluated via our metrics in the final experimental section.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A Review of Benchmarks for Visual Defect Detection in the Manufacturing Industry
The field of industrial defect detection using machine learning and deep learning is a subject of active research. Datasets, also called benchmarks, are used to compare and assess research results. There is a number of d…
Defect DetectionComponent-aware anomaly detection framework for adjustable and logical industrial visual inspection
Industrial visual inspection aims at detecting surface defects in products during the manufacturing process. Although existing anomaly detection models have shown great performance on many public benchmarks, their limite…
Anomaly ClassificationAnomaly DetectionSemantic SegmentationUnsupervised Semantic SegmentationTowards automatic visual inspection: A weakly supervised learning method for industrial applicable object detection
Industrial visual detection is an essential part in modern industry for equipment maintenance and inspection. With the recent progress of deep learning, advanced industrial object detectors are built for smart industrial…
Deep LearningDiversityobject-detectionObject Detection+2Anomaly Detection for Industrial Applications, Its Challenges, Solutions, and Future Directions: A Review
Anomaly detection from images captured using camera sensors is one of the mainstream applications at the industrial level. Particularly, it maintains the quality and optimizes the efficiency in production processes acros…
Anomaly DetectionSynthRender and IRIS: Open-Source Framework and Dataset for Bidirectional Sim-Real Transfer in Industrial Object Perception
Object perception is fundamental for tasks such as robotic material handling and quality inspection. However, modern supervised deep-learning models require large annotated datasets for robust automation under semi-uncon…
Synthetic Data GenerationImage Generation