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dc.contributor.author | Tepliukh, Yur![]() |
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dc.date.accessioned | 2024-02-15T10:41:36Z | |
dc.date.available | 2024-02-15T10:41:36Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Tepliukh, Yur. Template-based color correction in alternating lighting conditions / Tepliukh, Yur; Supervisor: Oles Dobosevych; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2020. – 29 p. | uk |
dc.identifier.uri | https://er.ucu.edu.ua/handle/1/4526 | |
dc.language.iso | en | uk |
dc.title | Template-based color correction in alternating lighting conditions | uk |
dc.type | Preprint | uk |
dc.status | Публікується вперше | uk |
dc.description.abstracten | Having the right colors is one of the best ways for picture to look good. But not only humans’ eye will appreciate correctly colored image, but also a computer, es- pecially when the task is to track object by its color. While this might not seem like a difficult one, but when you have really long-term tracking, in an environment where lightning conditions change over time, you want to be sure that your algorithm is still able to find desired object. Or maybe you cannot or don’t want to manually ad- just camera color settings, but still need to track same object during the day, sunset and in the afternoon, when everything changes it colors to red and blue afterwards. The main idea behind this work is to create an automatic pipeline which will output either corrected image, or the mask, which should be applied to produce cor- rected image, depending on selected method. This is achieved by using a template with reference color values, which is then compared with the colors on the input im- age and proceeded to color estimation algorithms. Different types of templates and color estimation algorithms were compared to select the most effective to provide color stability. We show that you don’t need a special templates to achieve good results in color calibration. | uk |