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dc.contributor.authorMuthukaruppan, Kartigayan
dc.contributor.authorNagarajan, R.
dc.contributor.authorSazali, Yaacob
dc.contributor.authorPandian, Paulraj
dc.contributor.authorMohamed Rizon, Mohamed Juhari
dc.date.accessioned2008-09-16T06:46:19Z
dc.date.available2008-09-16T06:46:19Z
dc.date.issued2005
dc.identifier.citationJournal of Engineering Research and Education, vol. 2, 2005, pages 17-29.en_US
dc.identifier.issn1823-2981
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/2288
dc.descriptionLink to publisher's homepage at http://jere.unimap.edu.myen_US
dc.description.abstractIn this paper, an industrial machine vision system incorporating Optical Character Recognition (OCR) is employed to inspect the marking on the Integrated Circuit (IC) Chips. This inspection is carried out while the ICs are coming out from the manufacturing line. A TSSOP-DGG type of IC package from Texas Instrument is used in this investigation. The IC chips markings are laser printed. This inspection system tests are laser printed marking on IC chips and are according to the specifications. Artificial intelligence (AI) techniques are used in this inspection. AI techniques utilized are neural network and fuzzy logic. The inspection is earned out to find the print errors; such as illegible character, upside down print and missing characters. The vision inspection of the printed markings on the IC chip is carried out in three phases, namely, image preprocessing, feature extraction and classification. MATLAB platform and its toolboxes are used for designing the inspection processing technique. The percentage of accuracy of the classification is found to be between 97% -100%.en_US
dc.language.isoenen_US
dc.publisherKolej Universiti Kejuruteraan Utara Malaysiaen_US
dc.subjectIntegrated circuitsen_US
dc.subjectArtificial intelligenceen_US
dc.subjectOptical Character Recognition (OCR)en_US
dc.subjectOptical character recognition devicesen_US
dc.subjectIntegrated circuits -- Inspectionen_US
dc.subjectIntegrated circuits -- Design and constructionen_US
dc.titleArtificial intelligence techniques in IC chip markingen_US
dc.typeArticleen_US
dc.identifier.urlhttp://jere.unimap.edu.myen_US


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