DocumentCode :
2726945
Title :
Automatic cartridge case image mosaic using SIFT and graph transformation matching
Author :
Feng, Zijun ; Luo, Man ; Chang, Shu ; Yang, Li ; Kong, Jun
Author_Institution :
Comput. Sch., Northeast Normal Univ., Changchun, China
Volume :
4
fYear :
2009
fDate :
20-22 Nov. 2009
Firstpage :
371
Lastpage :
375
Abstract :
Characteristic marks on the cartridge can be viewed as a ¿fingerprint¿ for identification of a firearm. Sometimes, however, not all information can be obtained from just one image due to the limitations of microscope and the unsmoothed specimen surface in the cartridge case image detection. Image mosaic that refers to the combination of two or more images into a single composite image is precisely to solve this problem. This paper proposes a new cartridge case image mosaic approach by using automatic image registration and fusion techniques. In the registration stage, the scale invariant feature transform (SIFT) is employed to obtain initial matching. Then the graph transformation matching (GTM) is used to remove incorrect matches effectively. In the fusion stage, histogram matching is applied to smooth seams which exist in the stitched image. Finally, a stitched image is obtained, which contains more information than each of the two original images. Experimental results demonstrate for cartridge case image mosaic in both subjective and objective evaluations.
Keywords :
graph theory; image fusion; image matching; image registration; image segmentation; transforms; SIFT; automatic cartridge case image mosaic; cartridge case image detection; fingerprint identification; graph transformation matching; image fusion; image registration; scale invariant feature transform; unsmoothed specimen surface; Decision support systems; Virtual reality; SIFT; cartridge case image; graph transformation matching; image fusion; image mosaic; image registration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
Type :
conf
DOI :
10.1109/ICICISYS.2009.5357672
Filename :
5357672
Link To Document :
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