MID-INFRARED (MIR) OCT-based inspection in industry
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arXiv
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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916820875739136 |
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| author | García-de-la-Puente, N. P. del Amor, Rocío García-Torres, Fernando Israelsen, Niels Møller Lapre, Coraline Petersen, Christian Rosenberg Bang, Ole Brouczek, Dominik Schwentenwein, Martin Neumann, Kevin Benson, Niels Naranjo, Valery |
| author_facet | García-de-la-Puente, N. P. del Amor, Rocío García-Torres, Fernando Israelsen, Niels Møller Lapre, Coraline Petersen, Christian Rosenberg Bang, Ole Brouczek, Dominik Schwentenwein, Martin Neumann, Kevin Benson, Niels Naranjo, Valery |
| contents | This paper aims to evaluate mid-infrared (MIR) Optical Coherence Tomography (OCT) systems as a tool to penetrate different materials and detect sub-surface irregularities. This is useful for monitoring production processes, allowing Non-Destructive Inspection Techniques of great value to the industry. In this exploratory study, several acquisitions are made on composite and ceramics to know the capabilities of the system. In addition, it is assessed which preprocessing and AI-enhanced vision algorithms can be anomaly-detection methodologies capable of detecting abnormal zones in the analyzed objects. Limitations and criteria for the selection of optimal parameters will be discussed, as well as strengths and weaknesses will be highlighted. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_01074 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | MID-INFRARED (MIR) OCT-based inspection in industry García-de-la-Puente, N. P. del Amor, Rocío García-Torres, Fernando Israelsen, Niels Møller Lapre, Coraline Petersen, Christian Rosenberg Bang, Ole Brouczek, Dominik Schwentenwein, Martin Neumann, Kevin Benson, Niels Naranjo, Valery Image and Video Processing Computer Vision and Pattern Recognition This paper aims to evaluate mid-infrared (MIR) Optical Coherence Tomography (OCT) systems as a tool to penetrate different materials and detect sub-surface irregularities. This is useful for monitoring production processes, allowing Non-Destructive Inspection Techniques of great value to the industry. In this exploratory study, several acquisitions are made on composite and ceramics to know the capabilities of the system. In addition, it is assessed which preprocessing and AI-enhanced vision algorithms can be anomaly-detection methodologies capable of detecting abnormal zones in the analyzed objects. Limitations and criteria for the selection of optimal parameters will be discussed, as well as strengths and weaknesses will be highlighted. |
| title | MID-INFRARED (MIR) OCT-based inspection in industry |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2507.01074 |