A Real-Time Image Mosaic Algorithm Based on Förstner Operator

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Image mosaic technology is becoming a new research hotspot of computer vision and artificial Intelligence. However, the existing image mosaic algorithms can’t meet the real time requirement of practical situation, the effective application of this technology is limited. This paper combined Förstner operator with the Gaussian image pyramid model and introduced them to the image mosaic technology for high real-time performance of the new image mosaic algorithm. The high-efficiency of the new algorithm has been verified by the experimental results.

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139-144

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October 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Förstner, W., & Gülch, E. (1987, June). A fast operator for detection and precise location of distinct points, corners and centres of circular features. InProc. ISPRS intercommission conference on fast processing of photogrammetric data (pp.281-305.

Google Scholar

[2] Rodehorst, V., & Koschan, A. (2006, March). Comparison and evaluation of feature point detectors. In Proc. 5th International Symposium Turkish-German Joint Geodetic Days" Geodesy and Geoinformation in the Service of our Daily Life", Berlin, Germany.

Google Scholar

[3] Remondino, F. (2006). Detectors and descriptors for photogrammetric applications. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36(3), 49-54.

Google Scholar

[4] Lowe, D. G. (1999). Object recognition from local scale-invariant features. InComputer vision, 1999. The proceedings of the seventh IEEE international conference on (Vol. 2, pp.1150-1157). IEEE.

DOI: 10.1109/iccv.1999.790410

Google Scholar

[5] Harris, C., & Stephens, M. (1988, August). A combined corner and edge detector. In Alvey vision conference (Vol. 15, p.50).

DOI: 10.5244/c.2.23

Google Scholar

[6] Zhang, Z. (2000). A flexible new technique for camera calibration. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 22(11), 1330-1334.

DOI: 10.1109/34.888718

Google Scholar

[7] David A. Forsyth and Jean Ponce. Computer Vision: A Modern Approach[M]. Publishing House of Electronics Industry. (2004).

Google Scholar

[8] Shi Lu , Su Gang and Han Fei. An Improved Algorithm Based on SIFT and Surf Image Stitching Algorithm[J]. Computer Application and Software. 2013, 30(6).

Google Scholar

[9] Li YUN-xia, Zeng Yi, Zhong Rui-yan and Guo Tao. Algorithm of Image Sitching Based on SIFT Feature Matching[J]. Computer Technology and Development. 2009, 19(1).

Google Scholar