Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/7366
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dc.contributor.authorGajjar, Ruchi-
dc.contributor.authorZaveri, Tanish-
dc.contributor.authorShukla, Ami-
dc.date.accessioned2017-02-07T06:15:00Z-
dc.date.available2017-02-07T06:15:00Z-
dc.date.issued2015-11-26-
dc.identifier.citation5th International Conference on Current Trends in Technology, NUiCONE - 2015, Institute of Technology, Nirma University, November 26 – 28, 2015en_US
dc.identifier.issn978-1-4799-9991-0/15/$31.00 ©2015 IEEE-
dc.identifier.urihttp://hdl.handle.net/123456789/7366-
dc.description.abstractExtraction of information from an image acquired by real imaging systems is a difficult task, since the observed image may be degraded by blurring. In this paper, a framework for classification of blur in an image is presented and a technique for classification of blur using invariants is proposed. In this method, the blur classification is carried out without estimating the blurring function. The proposed technique is applied on a large dataset of images degraded by motion blur, Gaussian blur and defocus blur. The simulation results show that the proposed method gives accurate classification of the blur present in an image.en_US
dc.publisherInstitute of Technology, Nirma University, Ahmedabaden_US
dc.relation.ispartofseriesITFEC038-4;-
dc.subjectBlur Classificationen_US
dc.subjectBlur Invariantsen_US
dc.subjectCombined Blur and Affine Invariantsen_US
dc.subjectImage Bluren_US
dc.subjectMoment Invariantsen_US
dc.subjectEC Faculty Paperen_US
dc.subjectFaculty Paperen_US
dc.subjectITFEC038en_US
dc.subjectITFEC008en_US
dc.titleInvariants Based Blur Classification Algorithmen_US
dc.typeFaculty Papersen_US
Appears in Collections:Faculty Papers, EC

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