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On testing image processing applications with statistical methods

dc.contributor.authorMayer, Johannes
dc.contributor.editorLiggesmeyer, Peter
dc.contributor.editorPohl, Klaus
dc.contributor.editorGoedicke, Michael
dc.date.accessioned2019-10-11T08:47:59Z
dc.date.available2019-10-11T08:47:59Z
dc.date.issued2005
dc.description.abstractTesting image processing applications is very ressource consuming. Many complex images have to be generated as test inputs and the expected resulting outputs have to be determined to complete the test cases. The present paper deals with this challenge in testing implementations of image operations, namely dilation. It applies random testing using models from stochastic geometry for random input generation. The Statistical Oracle, a modification of the well-known Heuristic resp. Parametric Oracle, is used to compare the results. Therefore, reliability predictions are also possible.en
dc.identifier.isbn3-88579-393-8
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/28335
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftware Engineering 2005
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-64
dc.titleOn testing image processing applications with statistical methodsen
dc.typeText/Conference Paper
gi.citation.endPage78
gi.citation.publisherPlaceBonn
gi.citation.startPage69
gi.conference.date8.-11.03.2005
gi.conference.locationEssen
gi.conference.sessiontitleRegular Research Papers

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