Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/75397
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dc.contributor.authorTan, Jun Hao-
dc.date.accessioned2018-05-31T03:22:58Z-
dc.date.available2018-05-31T03:22:58Z-
dc.date.issued2018-
dc.identifier.urihttp://hdl.handle.net/10356/75397-
dc.description.abstractIn the current Third Industrial Revolution, Image Registration is often used in the area such as X-ray Images, Satellites Images (Earth, Planets and Monitoring of Space) and Real Time Motion Tracking to enhance life by Research and Development (R&D). Basically, Image Registration is a process whereby multiple images which overlapping areas are being “combined” or “stitched” into one. Therefore, the quality of the result produced depends on the feature detection. Although there are many detection techniques available, each has its advantages and disadvantages for different type of features. For this project, a detection technique called the Speeded Up Robust Features (SURF) will be used. It is a modified technique much faster than Scale Invariant Features Transform (SIFT). Furthermore, M-Estimator will be used for detection of inliers and outliers. Similarly, the M-estimator is a modified technique of the Random Sample Consensus (RANSAC).en_US
dc.format.extent48 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University-
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleImage registrationen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorChua Chin Sengen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
item.grantfulltextrestricted-
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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