{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T16:48:34Z","timestamp":1778086114264,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T00:00:00Z","timestamp":1691971200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>A novelty signal processing method is proposed for a technical vision system (TVS). During data acquisition of an optoelectrical signal, part of this is random electrical fluctuation of voltages. Information theory (IT) is a well-known field that deals with random processes. A method based on using of the Shannon Entropy for feature extractions of optical patterns is presented. IT is implemented in structural health monitoring (SHM) to augment the accuracy of optoelectronic signal classifiers for a metrology subsystem of the TVS. To enhance the TVS spatial coordinate measurement performance at real operation conditions with electrical and optical noisy environments to estimate structural displacement better and evaluate its health for a better estimation of structural displacement and the evaluation of its health. Five different machine learning (ML) techniques are used in this work to classify optical patterns captured with the TVS. Linear predictive coding (LPC) and Autocorrelation function (ACC) are for extraction of optical patterns. The Shannon entropy segmentation (SH) method extracts relevant information from optical patterns, and the model\u2019s performance can be improved. The results reveal that segmentation with Shannon\u2019s entropy can achieve over 95.33%. Without Shannon\u2019s entropy, the worst accuracy was 33.33%.<\/jats:p>","DOI":"10.3390\/e25081207","type":"journal-article","created":{"date-parts":[[2023,8,14]],"date-time":"2023-08-14T10:13:57Z","timestamp":1692008037000},"page":"1207","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Shannon Entropy Used for Feature Extractions of Optical Patterns in the Context of Structural Health Monitoring"],"prefix":"10.3390","volume":"25","author":[{"given":"Wendy","family":"Garcia-Gonz\u00e1lez","sequence":"first","affiliation":[{"name":"Engineering Faculty, Universidad Aut\u00f3noma de Baja California, Mexicali 21280, BC, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1477-7449","authenticated-orcid":false,"given":"Wendy","family":"Flores-Fuentes","sequence":"additional","affiliation":[{"name":"Engineering Faculty, Universidad Aut\u00f3noma de Baja California, Mexicali 21280, BC, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4270-6872","authenticated-orcid":false,"given":"Oleg","family":"Sergiyenko","sequence":"additional","affiliation":[{"name":"Engineering Institute, Universidad Aut\u00f3noma de Baja California, Mexicali 21100, BC, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1830-0226","authenticated-orcid":false,"given":"Julio C.","family":"Rodr\u00edguez-Qui\u00f1onez","sequence":"additional","affiliation":[{"name":"Engineering Faculty, Universidad Aut\u00f3noma de Baja California, Mexicali 21280, BC, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0618-0455","authenticated-orcid":false,"given":"Jes\u00fas E.","family":"Miranda-Vega","sequence":"additional","affiliation":[{"name":"Department of Computer Systems, Tecnol\u00f3gico Nacional de M\u00e9xico, IT de Mexicali, Mexicali 21376, BC, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0055-4797","authenticated-orcid":false,"given":"Daniel","family":"Hern\u00e1ndez-Balbuena","sequence":"additional","affiliation":[{"name":"Engineering Faculty, Universidad Aut\u00f3noma de Baja California, Mexicali 21280, BC, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dutta, P., Aoki, P.M., Kumar, N., Mainwaring, A., Myers, C., Willett, W., and Woodruff, A. 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