Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/53262
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dc.contributor.authorChan, Zhi Xian.
dc.date.accessioned2013-05-31T03:00:37Z
dc.date.available2013-05-31T03:00:37Z
dc.date.copyright2013en_US
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/10356/53262
dc.description.abstractThe project shows a method of recognizing different tree diseases based on distance via using image processing. The following technique is being used was by partitioning each image into sub regions and compute histograms of local features found inside individual sub regions. Any interesting points on the object can be extracted to provide a feature description of it. Hence, Bag-of-features model is used to represent as an unordered collection of words and it has been widely used for computer vision. However, Spatial Pyramid is a better extension of an orderless Bag-of-Words which shows significant improvement of performance. To perform recognition, the features extracted from the training image are feed into Support Vector Machine for data classification. Based on the data classification, we would be able to see which type of trees diseases on highest accuracy.en_US
dc.format.extent39 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleRecognizing tree diseases at a distance via image processing and computer visionen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
dc.contributor.supervisor2Ast/P Wang Gangen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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