Abstract
Automation techniques have increased their applications in different areas of knowledge areas. Digital Image Processing is one of the most important application areas. Image processing algorithms have been developed to automate autofocus in digital cameras, to evaluate focus quality, and many other industrial automation tasks. In scientific use, image fidelity is determinative as blurred pictures may induce erroneous conclusions on imaged-object size, position, shape, and volume evaluation. For this reason, plenty of algorithms have been created to avoid these mistakes and to ensure a precise focus. However, these new algorithms’ uprising has produced some contradictory results. To solve these inconsistencies, the use of Paraconsistent Logic (PL) can be an important method to provide parameters to measure lack of information, indicating a paracomplete condition. Images with cylindrical refraction effects are important examples of how PL can be applied to solve focus inconsistencies. This work analyses experimental acquired images from objects inside glass cylindrical tube typically used in a natural circulation facility. This experiment is used as basis to exemplify the importance of using PL to evaluate different focus measurements in order to obtain good flow parameters estimation. Some intelligent algorithms are used to predict and to correct these possible inconsistencies on optical distortion evaluation, which is directly related to focus definition and estimation. As a result, object dimensions estimation can have its accuracy enhanced.
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Authors would like to thank the support of Fundação de Inovação e Pesquisa (FINEP), project 01.10.0248.00, with the Comissão Nacional de Energia Nuclear (CNEN).
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Masotti, P.H.F., de Mesquita, R.N. (2015). Paraconsistent Logic Study of Image Focus in Cylindrical Refraction Experiments. In: Abe, J. (eds) Paraconsistent Intelligent-Based Systems. Intelligent Systems Reference Library, vol 94. Springer, Cham. https://doi.org/10.1007/978-3-319-19722-7_8
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DOI: https://doi.org/10.1007/978-3-319-19722-7_8
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