Image Mosaic Based on Improved SIFT

Abstract:

Feature matching used in SIFT methods to extracting feature points, is the key of image mosaic. The advantages of SIFT is one of the most robust and the widely used image matching algorithms based on local features, which ensure the good mosaic image and reliable result. In this paper, we proposed a new image mosaic technology based on simple, which can solve massive calculation and long processing time produced by SIFT. The first step from this method is that 32 vectors, from the feature points, reduce to 16 vectors, and the feature points with 16 vectors construction a pot set, which is the space transformation matrix. And space transformation, the transformation is the mapping of the two images. The processed image is edge processed to eliminate image edge ambiguity and the right results is also rests on cluster .The stitched image is achieved thorough it. Experimental results show that the proposed algorithm is effective and comparing favorable with existing techniques, Practical application shows that this method also proposes a reliable parameter estimation method, and the result is reliable to stitching a large image. At the same time, the processing time is faster than SIFT.

• Periodical: Advanced Materials Research (Volumes 760-762)
• Pages: 1594-1598
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.760-762.1594
• Online since: September 2013
• Authors: Yan Wei Wang, Bing Lin, Hua Dong Sun
• Keywords: Characteristic Points, Image Matching, Image Mosaic, Image Registration, SIFT

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