{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T10:40:51Z","timestamp":1651056051409},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2016,12,30]],"date-time":"2016-12-30T00:00:00Z","timestamp":1483056000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>A general methodology is introduced for texture segmentation in binary, scalar, or multispectral\nimages. Textural information is obtained from morphological operations on images. Starting from a fine partition\nof the image in regions, hierarchical segmentations are designed in a probabilistic framework by means\nof probabilistic distances conveying the textural or morphological information, and of random markers accounting\nfor the morphological content of the regions and of their spatial arrangement. The probabilistic\nhierarchies are built from binary or multiple fusion of regions.<\/jats:p>","DOI":"10.1515\/mathm-2016-0012","type":"journal-article","created":{"date-parts":[[2017,1,3]],"date-time":"2017-01-03T10:00:33Z","timestamp":1483437633000},"source":"Crossref","is-referenced-by-count":1,"title":["Morphological probabilistic hierarchies for\ntexture segmentation"],"prefix":"10.1515","volume":"1","author":[{"given":"Dominique","family":"Jeulin","sequence":"first","affiliation":[{"name":"MINES ParisTech, PSL Research University, CMM-Centre de Morphologie Math\u00e9matique, 35, rue Saint Honor\u00e9, F-77305 Fontainebleau, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2016,12,30]]},"container-title":["Mathematical Morphology - Theory and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/mathm.2016.1.issue-1\/mathm-2016-0012\/mathm-2016-0012.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mathm-2016-0012\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mathm-2016-0012\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T10:20:09Z","timestamp":1651054809000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mathm-2016-0012\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,30]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2016,3,30]]}},"alternative-id":["10.1515\/mathm-2016-0012"],"URL":"https:\/\/doi.org\/10.1515\/mathm-2016-0012","relation":{},"ISSN":["2353-3390"],"issn-type":[{"value":"2353-3390","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,12,30]]}}}