Image Mosaic Method Based on SIFT Features of Line Segment | Zendy

Jun Zhu | Zendy; Mingwu Ren | Zendy

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Image Mosaic Method Based on SIFT Features of Line Segment

Author(s) -

Jun Zhu,

Mingwu Ren

Publication year - 2014

Publication title -

computational and mathematical methods in medicine

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.462

H-Index - 48

eISSN - 1748-6718

pISSN - 1748-670X

DOI - 10.1155/2014/926312

Subject(s) - scale invariant feature transform , ransac , artificial intelligence , computer vision , computer science , robustness (evolution) , line segment , rotation (mathematics) , mosaic , translation (biology) , scaling , pattern recognition (psychology) , feature (linguistics) , image (mathematics) , mathematics , history , biochemistry , chemistry , linguistics , geometry , philosophy , gene , archaeology , messenger rna

This paper proposes a novel image mosaic method based on SIFT (Scale Invariant Feature Transform) feature of line segment, aiming to resolve incident scaling, rotation, changes in lighting condition, and so on between two images in the panoramic image mosaic process. This method firstly uses Harris corner detection operator to detect key points. Secondly, it constructs directed line segments, describes them with SIFT feature, and matches those directed segments to acquire rough point matching. Finally, Ransac method is used to eliminate wrong pairs in order to accomplish image mosaic. The results from experiment based on four pairs of images show that our method has strong robustness for resolution, lighting, rotation, and scaling.

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