Comparison of selected image processing techniques

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dc.contributor.authorAdewole, A.P.
dc.contributor.authorMustapha, M.O.
dc.date.accessioned2019-09-10T12:21:21Z
dc.date.available2019-09-10T12:21:21Z
dc.date.issued2014
dc.descriptionStaff publicationsen_US
dc.description.abstractImage as an important artifact faced with several constraints that may inhibit its usefulness. These constraints includes noise, Identification of objects in the image and extraction of features. In this paper, the denoising methods of Two Stages Image Denoising By Principal Component Analysis With Local Pixel Grouping(PCA - LPG) and Non Linear Filtering Algorithm For Underwater Images, the object identification methods of SCALE-INVARIANT FEATURE TRANSFORM (SIFT) and SPEEDED UP ROBUST FEATURES (SURF), the feature extraction methods of thresholding and subtraction and template matching are compared experimentally The experimental evaluation of these algorithms made it possible to draw some conclusions. These conclusions are supported from the results of the implementations of each technique, hence the recommended technique for denoising is Local Pixel Grouping (PCA - LPG), the recommended technique for object identification is SPEEDED UP ROBUST FEATURES (SURF) and the recommended technique for feature extraction is tresholding and subtraction. The recommended techniques for each of the concept were implemented in C# programming language with the help of an open source computer vision library EmguCV.en_US
dc.identifier.citationAdewole A.P, and Mustapha, M.O. (2014). Comparison of selected image processing techniques. Lautech Journal of engineering and Technology. Vol.8(2):1-9pp.en_US
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/5465
dc.language.isoenen_US
dc.publisherLautech Journal of engineering and Technologyen_US
dc.relation.ispartofseriesLautech Journal of engineering and Technology;Vol.8(2)
dc.subjectPrincipal Component Analysisen_US
dc.subjectLocal Pixel Groupingen_US
dc.subjectDenoisingen_US
dc.subjectFeature Extrationen_US
dc.subjectNon Linear Filteringen_US
dc.subjectObject Identificationen_US
dc.subjectScale-invariant feature transformen_US
dc.subjectSpeeded up robust featuresen_US
dc.subjectImage Processing Algorithmsen_US
dc.subjectResearch Subject Categories::TECHNOLOGY::Information technology::Computer science::Computer scienceen_US
dc.titleComparison of selected image processing techniquesen_US
dc.typeArticleen_US
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