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A robust technique for image mosaicing using modified SIFT
In this paper a robust technique is used for image mosaicing to reduce the computational time and increase the efficiency through modified Scale Invariant Feature Transform SIFT. Modified Scale Invariant Feature Transform algorithm is used to increase the efficiency and to reduce the computational time. In this normalized cross correlation is used to find the best possible match for the image warping. Area found by Normalized Cross Correlation is used for feature matching, through this method computational time is reduced. Two different methods are combined to get the best output. As the number of matches increased the efficiency of the algorithm also increased. The area for matching is reduced so the computational time gets reduced. The output mosaicked image is warped by the best possible matches This paper depicts the implementation of the real images click by a normal Samsung phone camera at different angles and locations. Homography is used to find the angular relation between the images. Normalized Modified SIFT algorithm is used to increase the efficiency and reduce the computational time. Mosaiced image is efficient enough as compare to SIFT algorithm.
Computational Time, Efficiency, Image Mosaicing, Modified Scale Invariant Feature Transform (SIFT) Algorithm, Normalized Cross Correlation.
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