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Author: search.filters.author.Chunhavittayatera, SiwaphonSubject: search.filters.subject.Phase correlation

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    Image registration using hough transform, phase correlation and best-first search algorithm
    (2007-12-01)
    Chunhavittayatera, Siwaphon
    ;
    Chitsobhuk, Orachat
    This paper presents image registration using a combination of Hough transform, phase correlation and best-first search algorithm to estimate rotation and translation parameters. These parameters are used to register input images and create a seamless representation of the registered image. In the first step, the translation of angles are pre-calculated based on ID phase correlation in Hough space and used as candidate angles. Then, best-first search algorithm is applied to obtain the best translation of angle from candidate angles, which is used to de-rotated the input images. In the second step, the translation in x-y axis is computed using 2D phase correlation. Finally, the input images are registered using the estimated translation parameter. The experimental results using various image details and sizes show the accuracy of the proposed technique to detect the translation parameters. The best-first search algorithm can help to increase the precision of rotation parameter after Hough transform and phase correlation while require less amount of processing time compared to full search algorithm.
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    Image registration using Hough transform and phase correlation
    (2006-01-01)
    Chunhavittayatera, Siwaphon
    ;
    Chitsobhuk, Orachat
    ;
    Tongprasert, Kiatnarong
    This paper presents image registration using a combination of Hough transform and phase correlation technique in Fourier domain to estimate rotation and translation parameters. These paramters are used to register input images and create a seamless representation of the registered image. The first step is based on 1D phase correlation which calculates the translation of angle in Hough space, obtained form Hough transform. The rotation parameter obtain from this step is used to de-rotated the input images. The second step provides the translation in x-y axis using 2D phase correlation. Finally, the input images are registered using the estimated translation parameter. The experimental results show the accuracy of the proposed method to detect the translation parameters and find the relevant potential angles of rotation for various image details and sizes. The proposed method is ease to operation, less computation complexity, thus requires less amount of process time due to the high efficiency of fast Fourier transform (FFT).