DocumentCode
493578
Title
Image Matching Based on Local Invariant Feature and Histogram-Based Similar Distance
Author
Shan, Baoming ; Cui, Fengying
Author_Institution
Coll. of Autom. & Electron. Eng., Qingdao Univ. of Sci. & Technol., Qingdao
Volume
1
fYear
2009
fDate
7-8 March 2009
Firstpage
1030
Lastpage
1033
Abstract
In this paper we present a novel approach combining local invariant feature descriptor ARPIH (Angular Radial Partitioning Intensity Histogram) with histogram-based similar distance (HSD). The method succeeds the descriptorpsilas distinctiveness and provides higher robustness for image deformations, such as rotation, illumination changing and perspective, etc. We present the HSD to calculate the number of the similar points between template image and target image in order to decrease the calculation complicacy and improve the matching precision. The matching results show good performance of our approach for both geometric deformations and illumination changing.
Keywords
deformation; image matching; angular radial partitioning intensity histogram; histogram-based similar distance; image deformation; image matching; local invariant feature; target image; template image; Biomedical imaging; Computer science; Computer science education; Educational institutions; Educational technology; Gray-scale; Histograms; Image matching; Lighting; Robustness; ARPIH; HSD; image matching; local invariant feature;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science, 2009. ETCS '09. First International Workshop on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-1-4244-3581-4
Type
conf
DOI
10.1109/ETCS.2009.235
Filename
4958939
Link To Document