2014 · 24 citations · 4 references
ComputingComputer Science3D ModelingComputer VisionMachine VisionFeature DescriptionFeature DetectionFeature TransformationImage RegistrationObject RecognitionPattern RecognitionFeature MatchingImage MatchingRegistrationRobustness To Illumination ChangesScale-invariant Feature DetectionScale-invariant Feature TransformScale-invariant Feature Transform (Sift)Scale-invariant Matching
This paper presents Image matching and registration method that is invariant to scale, rotation, translation and illumination changes. The method is named as Scale Invariant Feature Transform (SIFT). This algorithm will detect and describe image features such as contours, points, corners etc. SIFT descriptors are the characteristic signature of the feature. The features calculated from the image to be registered should be distinctive and then it can be matched. It can be useful in object recognition, image mosaicing, 3 D reconstruction and video tracking. The simulation results shows that this algorithm works well in all types of cases having scale and rotation difference, it also register the object having occlusion and clutter background.
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Image registration using robust M-estimators
K. V. Arya, P. Gupta, Prem Kalra et al. · Pattern Recognition Letters · 2007 · 47 citations
Automatic Image Registration using SIFT-NCC
Vinividyadharan, Subusurendran · 2012 · 11 citations