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In Filtering contrast, brightness and normalization of the image are
\n\nperformed with an ultimate goal to remove or reduce the noise to a maximum extent.
\n\nContrast and Brightness are two major factors, which affect the superiority of an
\n\nimage for easy or stainless or pleasant viewing. Equalization through Histogram (HE)
\n\nis a very famous approach for image contrast adjustment or enhancement in image
\n\nprocessing. In general, the histogram equalization distributes pixel values consistently
\n\nand produces an outcome in a superior image with the linear increasing histogram.
\n\nContrast adjustment is the part of image preprocessing and specifically filtering noise.
\n\nIn this paper, the new algorithm is discussed for a Grayscale Fingerprint image. The
\n\nalgorithm tunes pixel intensity value to a higher intensity value based on a constant
\n\nvalue τ. In this paper, we compare the new algorithm with Histogram Equalization
\n\nand try to find its advantages and disadvantages. This method is effectively used in
\n\nFingerprint Identification/verification purpose as an alternative for image filtering.
\n\nThe algorithm is implemented using MATLAB2015a.
", "publication_date": "2018-01-15", "publisher": "Zenodo", "resource_type": { "id": "publication-article", "title": { "de": "Zeitschriftenartikel", "en": "Journal article" } }, "rights": [ { "description": { "en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited." }, "icon": "cc-by-icon", "id": "cc-by-4.0", "props": { "scheme": "spdx", "url": "https://creativecommons.org/licenses/by/4.0/legalcode" }, "title": { "en": "Creative Commons Attribution 4.0 International" } } ], "subjects": [ { "subject": "Contrast Adjustment, Fingerprint recognition, Grayscale Image, Histogram Equalization, Image filtering, MATLAB2015a" } ], "title": "A Novel Tuning Based Contrast Adjustment Algorithm for Grayscale Fingerprint Image" }, "parent": { "access": { "owned_by": { "user": 24257 } }, "communities": {}, "id": "1195704", "pids": { "doi": { "client": "datacite", "identifier": "10.5281/zenodo.1195704", "provider": "datacite" } } }, "pids": { "doi": { "client": "datacite", "identifier": "10.5281/zenodo.1195705", "provider": "datacite" }, "oai": { "identifier": "oai:zenodo.org:1195705", "provider": "oai" } }, "revision_id": 5, "stats": { "all_versions": { "data_volume": 11580866.0, "downloads": 22, "unique_downloads": 19, "unique_views": 45, "views": 45 }, "this_version": { "data_volume": 11580866.0, "downloads": 22, "unique_downloads": 19, "unique_views": 45, "views": 45 } }, "status": "published", "updated": "2020-01-20T13:59:34.575031+00:00", "versions": { "index": 1, "is_latest": true } }