Scholarlink

<p>In industrial applications, the growing relevance of large-scale metrology brings forth the challenge of achieving highly precise measurements (± 0.1&#xa0;mm) using solutions that are both cost-efficient and easy to operate. This paper explores the performance of Markerless Photogrammetry (MP) compared to established technologies like Coordinate Measuring Machines (CMM), Laser Trackers (LT), and Marker-based Photogrammetry (MbP) to evaluate MP’s potential in industrial tasks. Experimental results show that MP achieved mean distance errors between 0.26 and 0.94&#xa0;mm, higher than those obtained with CMM (&lt; 0.003&#xa0;mm) and LT (&lt; 0.05&#xa0;mm), but slightly superior to MbP in large-volume scenarios(&lt; 0.15&#xa0;mm). While CMM and LT deliver exceptional accuracy, their practicality is often restricted by the cost and limitations in large-volume parts. MbP stands out for its extensive range, adaptability, and user-friendliness, though it is confined to capturing sparse data and does not achieve the same level of accuracy as conventional methods. Although MP demonstrates lower accuracy with respect to CMM and LT, the results highlight its potential as a practical alternative for scenarios where affordability and ease of use outweigh the drawbacks of long computational requirements (up to 5&#xa0;h for complex models).</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Exploring markerless close-range photogrammetry for industrial inspection applications: a feasibility study

  • 期刊论文

  • 发表日期：

    2025年11月11日

查看全文
  • Inés Prieto,
  • Imanol Herrera,
  • Andrea Maria Lingua,
  • Pablo Puerto,
  • Ibai Leizea

摘要

In industrial applications, the growing relevance of large-scale metrology brings forth the challenge of achieving highly precise measurements (± 0.1 mm) using solutions that are both cost-efficient and easy to operate. This paper explores the performance of Markerless Photogrammetry (MP) compared to established technologies like Coordinate Measuring Machines (CMM), Laser Trackers (LT), and Marker-based Photogrammetry (MbP) to evaluate MP’s potential in industrial tasks. Experimental results show that MP achieved mean distance errors between 0.26 and 0.94 mm, higher than those obtained with CMM (< 0.003 mm) and LT (< 0.05 mm), but slightly superior to MbP in large-volume scenarios(< 0.15 mm). While CMM and LT deliver exceptional accuracy, their practicality is often restricted by the cost and limitations in large-volume parts. MbP stands out for its extensive range, adaptability, and user-friendliness, though it is confined to capturing sparse data and does not achieve the same level of accuracy as conventional methods. Although MP demonstrates lower accuracy with respect to CMM and LT, the results highlight its potential as a practical alternative for scenarios where affordability and ease of use outweigh the drawbacks of long computational requirements (up to 5 h for complex models).