On testing image processing applications with statistical methods

dc.contributor.author	Mayer, Johannes
dc.contributor.editor	Liggesmeyer, Peter
dc.contributor.editor	Pohl, Klaus
dc.contributor.editor	Goedicke, Michael
dc.date.accessioned	2019-10-11T08:47:59Z
dc.date.available	2019-10-11T08:47:59Z
dc.date.issued	2005
dc.description.abstract	Testing 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.isbn	3-88579-393-8
dc.identifier.pissn	1617-5468
dc.identifier.uri	https://dl.gi.de/handle/20.500.12116/28335
dc.language.iso	en
dc.publisher	Gesellschaft für Informatik e.V.
dc.relation.ispartof	Software Engineering 2005
dc.relation.ispartofseries	Lecture Notes in Informatics (LNI) - Proceedings, Volume P-64
dc.title	On testing image processing applications with statistical methods	en
dc.type	Text/Conference Paper
gi.citation.endPage	78
gi.citation.publisherPlace	Bonn
gi.citation.startPage	69
gi.conference.date	8.-11.03.2005
gi.conference.location	Essen
gi.conference.sessiontitle	Regular Research Papers

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