Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41797
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dc.contributor.authorMohammad Zulhilmi, Ahmad Hisham-
dc.date.accessioned2016-06-01T02:27:48Z-
dc.date.available2016-06-01T02:27:48Z-
dc.date.issued2015-06-
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/41797-
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractThis paper proposes an automated system for recognizing insect species based on their shape. In this report, a Radon Transform shape descriptor is proposed to extract a projection according to a single angle. This projection is chosen in way that contains the necessary information to recognize an object. This descriptor (called RƟ-signature) provides global information of a binary shape regardless its form. The signature keeps fundamental geometrical transformation like scale, translation and rotation. Implemented insect recognition sample tested in used software environment and the test results were analyzed. The accuracy and the efficiency of the proposed algorithm in the presence of a variety of transformations are evaluated within a shape recognition process. This project will add an assistant feature of Neural Network Classifier tool, and this feature will effectively enhance the efficiency of retrieval in largest dataset.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subjectInsectsen_US
dc.subjectRecognition systemen_US
dc.subjectShape descriptoren_US
dc.subjectNeural Network Classifieren_US
dc.subjectRadon transformen_US
dc.titleInspect species recognition featuring projection-based shape descriptoren_US
dc.typeLearning Objecten_US
dc.contributor.advisorDr. Said Amirul Anwar Ab.Hamid@Ab. Majiden_US
dc.publisher.departmentSchool of Computer and Communication Engineeringen_US
Appears in Collections:School of Computer and Communication Engineering (FYP)

Files in This Item:
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Abstract,Acknowledgement.pdf244.68 kBAdobe PDFView/Open
Introduction.pdf219.62 kBAdobe PDFView/Open
Literature Review.pdf425.48 kBAdobe PDFView/Open
Methodology.pdf328.43 kBAdobe PDFView/Open
Results and Discussion.pdf481.9 kBAdobe PDFView/Open
Conclusion and Recommendation.pdf189.85 kBAdobe PDFView/Open
Refference and Appendics.pdf581.96 kBAdobe PDFView/Open


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