4.7 Review

A critical review for machining positioning based on computer vision

Journal

MEASUREMENT
Volume 184, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.measurement.2021.109973

Keywords

Visual positioning; Positioning processing; Optical system; Image preprocessing; Feature extraction

Funding

  1. Scientific and Technological Projects of Henan Province, China [202102210395]
  2. Scientific and Technological Innovation Team of Colleges and Universities in Henan Province, China [20IRTSTHN015]
  3. Local Innovative and Research Team Project of Guangdong Pearl River Talents Program, China [2017BT01G167]
  4. Natural Science Foundation of China [51975228]

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This study provides a comprehensive review of positioning methods for workpieces in machining using computer vision technology, covering key technologies in image acquisition, image preprocessing, feature extraction, and existing applications. The importance and application value of computer vision in machining are emphasized.
With the rapid development of science and technology, the manufacturing industry has to cope with increasingly stricter requirements in terms of the quality of processed products. To improve production flexibility and automation, computer vision is widely used in machining due to its safety, reliability, continuity, high accuracy, and real-time performance. In this study, a comprehensive review of positioning methods for workpieces in machining is presented from the perspective of computer vision technology. First, the key technologies in image acquisition are described in detail, and a analysis of different lighting modes is conducted. Second, image preprocessing is described by summarizing enhancement and image segmentation methods. Third, from the perspectives of accuracy and speed, feature extraction methods are compared and evaluated. Next, the existing applications of visual positioning technology in machining are discussed. Finally, the existing problems are summarized, and future research directions technology suggested.

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