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Author Holia, Mehfuza
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Affine Transformation ♦ V.k.t Hakar Image Registration ♦ Mehfuza Holia Dr ♦ Nelder Mead Simplex Method ♦ Original Image ♦ Sensed Image ♦ Different Time ♦ Image Registration ♦ Translation Parameter ♦ Coordinate System ♦ Function Minimization ♦ Nelder-mead Method ♦ Different View Point ♦ Different Sensor ♦ Important Problem ♦ Pixel Mapping Function ♦ Transformation Parameter ♦ Different Set ♦ Using Matlab ♦ Fundamental Task ♦ Reference Image ♦ Translation Difference ♦ Maximum Correlation ♦ Computer Vision System Set ♦ Different Coordinate System ♦ Simulation Result ♦ Pattern Image ♦ Different Measurement ♦ Different Perspective ♦ Similarity Transformation ♦ Image Processing Technique
Abstract In computer vision system sets of data acquired by sampling of the same scene or object at different times or from different perspectives, will be in different coordinate systems. Image registration is the process of transforming the different sets of data into one coordinate system. Registration is necessary in order to be able to compare or integrate the data obtained from different measurements such as different view points, different times, different sensors etc. Image Registration is an important problem and a fundamental task in image processing technique. This paper presents an algorithm for recovering translation parameter from two images that differ by Rotation, Scaling, Transformation and Rotation-scale-Translation (RST) also known as similarity transformation. It is a transformation expressed as a pixel mapping function that maps a reference image into a pattern image. The images having rotational, scaling, translation differences are registered using correlation with Nelder-mead method for function minimization. The algorithm finds the correlation between original image and sensed images. It applies the transformation parameters on sensed images so that maximum correlation between original image and sensed images are achieved. Simulation results (Using Matlab) on images show the Performances of the method.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article