{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:00:06Z","timestamp":1760148006995,"version":"build-2065373602"},"reference-count":44,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,3,19]],"date-time":"2023-03-19T00:00:00Z","timestamp":1679184000000},"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>In this paper, we propose an innovative approach to improve the performance of an Automatic Fingerprint Identification System (AFIS). The method is based on the design of a Possibilistic Fingerprint Quality Assessment (PFQA) filter where ground truths of fingerprint images of effective and ineffective quality are built by learning. The first approach, QS_I, is based on the AFIS decision for the image without considering its paired image to decide its effectiveness or ineffectiveness. The second approach, QS_PI, is based on the AFIS decision when considering the pair (effective image, ineffective image). The two ground truths (effective\/ineffective) are used to design the PFQA filter. PFQA discards the images for which the AFIS does not generate a correct decision. The proposed intervention does not affect how the AFIS works but ensures a selection of the input images, recognizing the most suitable ones to reach the AFIS's highest recognition rate (RR). The performance of PFQA is evaluated on two experimental databases using two conventional AFIS, and a comparison is made with four current fingerprint image quality assessment (IQA) methods. The results show that an AFIS using PFQA can improve its RR by roughly 10% over an AFIS not using an IQA method. However, compared to other fingerprint IQA methods using the same AFIS, the RR improvement is more modest, in a 5\u20136% range.<\/jats:p>","DOI":"10.3390\/e25030529","type":"journal-article","created":{"date-parts":[[2023,3,20]],"date-time":"2023-03-20T04:05:23Z","timestamp":1679285123000},"page":"529","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Innovative Possibilistic Fingerprint Quality Assessment (PFQA) Filter to Improve the Recognition Rate of a Level-2 AFIS"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9176-1785","authenticated-orcid":false,"given":"Houda","family":"Khmila","sequence":"first","affiliation":[{"name":"Control and Energy Management (CEM Lab), Sfax Engineering School, University of Sfax, BP W, Sfax 3038, Tunisia"},{"name":"Smart Aid Technologies SATECH, Sfax 3061, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Imene Khanfir","family":"Kallel","sequence":"additional","affiliation":[{"name":"Control and Energy Management (CEM Lab), Sfax Engineering School, University of Sfax, BP W, Sfax 3038, Tunisia"},{"name":"Smart Aid Technologies SATECH, Sfax 3061, Tunisia"},{"name":"Image & Information Processing Department (iTi), IMT-Atlantique, Technop\u00f4le Brest Iroise CS 83818, CEDEX, 29238 Brest, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9658-7595","authenticated-orcid":false,"given":"Eloi","family":"Boss\u00e9","sequence":"additional","affiliation":[{"name":"Image & Information Processing Department (iTi), IMT-Atlantique, Technop\u00f4le Brest Iroise CS 83818, CEDEX, 29238 Brest, France"},{"name":"Expertises Parafuse Inc., Quebec, QC G1W 4N1, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Basel","family":"Solaiman","sequence":"additional","affiliation":[{"name":"Image & Information Processing Department (iTi), IMT-Atlantique, Technop\u00f4le Brest Iroise CS 83818, CEDEX, 29238 Brest, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,19]]},"reference":[{"key":"ref_1","unstructured":"Garcia-Salicetti, S., Mellakh, M.A., Allano, L., and Dorizzi, B. 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