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Second, wavelet transform is used to extract discriminant feature from the LBP image. The experiment results on LFW, Extended YaleB and CMU-PIE face databases show that the proposed method outperforms several popular face recognition methods, and the preprocessing step plays an important role to extract effective features for classification. <\/jats:p>","DOI":"10.1142\/s0218001420500305","type":"journal-article","created":{"date-parts":[[2020,1,31]],"date-time":"2020-01-31T08:30:26Z","timestamp":1580459426000},"page":"2050030","source":"Crossref","is-referenced-by-count":6,"title":["A Feature Extraction Method based on Local Binary Pattern Preprocessing and Wavelet Transform"],"prefix":"10.1142","volume":"34","author":[{"given":"Peng-Yi","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Information Technology, Shanxi Professional College of Finance, Taiyuan, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0760-5286","authenticated-orcid":false,"given":"Zhi-Ming","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Applied Math, Shanxi University of Finance and Economics, Taiyuan, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2020,4,20]]},"reference":[{"key":"S0218001420500305BIB001","first-page":"469","volume-title":"Europe Conf. 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