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SCI."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Computer vision is vital for various applications like object tracking for autonomous driving or quality assurance. Hence, assuring that computer vision fulfills given quality criteria is essential and requires sufficient testing. In previous work, authors introduced a testing method relying on image modifications for a photometric stereo application. Image modifications include pixel errors or the rotation of images to be analyzed, revealing a substantial impact on the computed outcome of the photometric stereo application, depending on the applied modification. This paper focuses on two questions, i.e., (i) whether we can reproduce the impact of image modifications in a real-world setup and (ii) on the practicability of the application of photometric stereo in the application context of quality assurance of riblet surfaces. To answer the first question, we compare the impact of the rotation and light conditions of the analyzed sample with the rotation and light modification applied to the image of the sample. The comparison indicates a similar effect when using rotation and light modifications, showing that testing based on image modifications is valuable for verifying computer vision applications. For the second question, we outline a usage scenario, present experimental observations, and discuss a stochastical model, allowing us to confirm the experiments. Moreover, we outline what to expect when using the computer vision application for real quality assurance.<\/jats:p>","DOI":"10.1007\/s42979-024-03478-w","type":"journal-article","created":{"date-parts":[[2024,12,16]],"date-time":"2024-12-16T08:57:02Z","timestamp":1734339422000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evaluating Testing and Use of Photometric Stereo Applications for Riblet Inspection"],"prefix":"10.1007","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0462-2283","authenticated-orcid":false,"given":"Franz","family":"Wotawa","sequence":"first","affiliation":[]},{"given":"Ledio","family":"Jahaj","sequence":"additional","affiliation":[]},{"given":"Nicole","family":"Brosch","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,12,16]]},"reference":[{"key":"3478_CR1","volume-title":"Software Testing Techniques","author":"B Beizer","year":"1990","unstructured":"Beizer B. Software Testing Techniques. USA: Van Nostrand Reinhold Co.; 1990."},{"issue":"4\u20135","key":"3478_CR2","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1007\/s00502-018-0630-7","volume":"135","author":"F Wotawa","year":"2018","unstructured":"Wotawa F, Peischl B, Kl\u00fcck F, Nica M. Quality assurance methodologies for automated driving. Elektrotech Informationstechnik. 2018;135(4\u20135):322\u20137.","journal-title":"Elektrotech. Informationstechnik"},{"key":"3478_CR3","unstructured":"Wotawa F. On the importance of system testing for assuring safety of AI systems. In: AISafety@IJCAI. CEUR Workshop Proceedings, vol. 2419. CEUR-WS.org, Macao, China 2019;"},{"key":"3478_CR4","doi-asserted-by":"crossref","unstructured":"Kl\u00fcck F, Wotawa F, Neubauer G, Tao J, Nica M. Analysing experimental results obtained when applying search-based testing to verify automated driving functions. In: DSA, pp. 213\u2013219. 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Measurements of macroscopic and microscopic riblet defects and their impact on performance. In: Proceedings of the AIAA SCITECH 2022 Forum, vol. 37. San Diego, CA & Virtual 2022; https:\/\/doi.org\/10.2514\/6.2022-0916","DOI":"10.2514\/6.2022-0916"},{"key":"3478_CR8","doi-asserted-by":"publisher","unstructured":"Wotawa F, Klampfl L, Jahaj L. A framework for the automation of testing computer vision systems. In: 2021 IEEE\/ACM International Conference on Automation of Software Test (AST), 2021;121\u2013124. https:\/\/doi.org\/10.1109\/AST52587.2021.00023","DOI":"10.1109\/AST52587.2021.00023"},{"key":"3478_CR9","doi-asserted-by":"publisher","unstructured":"Wotawa F, Jahaj L. Testing photometric stereo applications. In: 2022 9th International Conference on Dependable Systems and Their Applications (DSA) 2022; https:\/\/doi.org\/10.1109\/DSA56465.2022.00029","DOI":"10.1109\/DSA56465.2022.00029"},{"key":"3478_CR10","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1007\/978-3-031-43240-8_3","volume-title":"Testing Software and Systems","author":"F Wotawa","year":"2023","unstructured":"Wotawa F, Jehaj L, Brosch N. On the evaluation of photometric stereo applications testing using image modifications. In: Bonfanti S, Gargantini A, Salvaneschi P, editors. Testing Software and Systems. Cham: Springer; 2023. p. 40\u201351."},{"key":"3478_CR11","doi-asserted-by":"crossref","unstructured":"Ikehata S. Cnn-ps: Cnn-based photometric stereo for general non-convex surfaces. In: Proceedings of the European Conference on Computer Vision (ECCV) 2018;","DOI":"10.1007\/978-3-030-01267-0_1"},{"key":"3478_CR12","doi-asserted-by":"publisher","unstructured":"Ikehata S, Wipf D, Matsushita Y, Aizawa K. 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