Rittavee Matungka

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Image registration is an essential step in many image processing applications that need visual information from multiple images for comparison, integration, or analysis. Recently, researchers have introduced image registration techniques using the log-polar transform (LPT) for its rotation and scale invariant properties. However, it suffers from nonuniform(More)
Object recognition is an essential task in many image processing applications. Although object appears as three-dimensional in real world, they are usually perceived as two-dimensional in digital image or video. In most cases, major problems in recognizing objects lie on the two-dimensional geometry changes in object appearances. This paper presents an(More)
This paper proposes a rotation and scale invariant object recognition method which combines image feature extraction in Cartesian coordinate with the log-polar mapping and similarity measure techniques for classification. The method yields robustness for fast computation without any rescale needed in the target image. The method also does not use motion(More)
Image registration is an essential step in many image processing applications that need visual information from multiple images for comparison, integration or analysis. Recently researchers have introduced image registration techniques using the log-polar transform (LPT) for its rotation and scale invariant properties. However, the accuracy of the approach(More)
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