Editing Visual inspection (section)

==Humorous terminology==
To do an '''eyeball search''' is to look for something specific in a mass of [[source code|code]] or data with [[human eye|one's own eyes]], as opposed to using some sort of [[pattern matching]] software like [[grep]] or any other automated search tool. Also known as '''vgrep''' or '''ogrep''', i.e., "visual/optical grep".<ref>''[[Jargon File]]'', version 4.4.6, 25 Oct 2003''
</ref> See also [[vdiff]].

"Eyeballing" is the most common and readily available method of initial data assessment.<ref>Srinika Jayaratne, Rona L. Levy (1979) "Empirical Clinical Practice", {{ISBN|0-231-04188-8}}, [https://books.google.com/books?id=tkQFKoyPsegC&dq=eyeballing&pg=PA110 p. 110]</ref> This method is effective for identifying patterns or anomalies in complex data but can be time-intensive and error-prone.<ref>{{cite journal |last1=Hrymak |first1=Victor |last2=Vries |first2=Jam |year=2019 |title=The development and trial of systematic visual search: a visual inspection method designed to improve current workplace risk assessment practice |journal=Policy and Practice in Health and Safety |volume=18 |issue=1 |pages=9-24 |publisher=Taylor & Francis|doi=10.1080/14773996.2019.1708615}}</ref> Although low-cost and adaptable, its efficiency and [[Return on investment|ROI]] often fall short compared to automated tools, which offer greater scalability and consistency.<ref>{{cite web |url=https://averroes.ai/blog/visual-inspection-system-cost-breakdown |title=Visual Inspection System Cost Breakdown & Calculating ROI |website=Averroes |date=Jun 18, 2024 |access-date=Nov 26, 2024}}</ref> However, switching from manual visual inspection to automated methods depends on the task's complexity, scale, and the balance between upfront costs and long-term efficiency.<ref>{{cite report |last1=Behrisch |first1=Michael |last2=Krueger |first2=Robert |year=2018 |title=Visual Pattern-Driven Exploration of Big Data |publisher=IEEE |location=Germany |pages=1-11 |doi=10.1109/BDVA.2018.8534028|arxiv=1807.01364 }}</ref>

Experts in [[pattern recognition]] maintain that the "eyeball" technique is still the most effective procedure for searching arbitrary, possibly unknown structures in data.<ref>Hans-Jürgen Zimmermann (2001) "Fuzzy Set Theory--and Its Applications", {{ISBN|0-7923-7435-5}}, [https://books.google.com/books?id=hz_mvNU8YHYC&dq=%22eyeball+search%22&pg=PA278 p. 278]</ref>

In the military, applying this sort of search to real-world terrain is often referred to as "using the '''Mark I Eyeball'''"  device (pronounced as Mark One Eyeball), the U.S. military adopting it in 1950s.<ref>"Contemporary Geodesy" (Proceedings of a Conference Held at the Harvard College Observatory - Smithsonian Astrophysical Observatory, Cambridge, MA, December 1–2, 1958). [https://books.google.com/books?id=vtg_AAAAIAAJ&q=%22mark+I+eyeball%22 P. 68] says: "Now the first type of optical tracking, the most elementary, is that using merely the naked eye — as I heard a Navy man say the other day, 'Mark I eyeball' ".</ref> The term is an allusion on military nomenclature, "Mark I" being the first version of a military vehicle or weapon.