Outlier-Resistant Dissimilarity Measure for Feature-based Image Matching

Author

Palenichka, Roman M. ; Lakhssassi, Ahmed ; Zaremba, Marek B.

Author_Institution

Univ. of Quebec in Outaouais, Gatineau, QC, Canada

fYear

2010

fDate

23-26 Aug. 2010

Firstpage

846

Lastpage

849

Abstract

A novel dissimilarity measure is proposed to perform correspondence image matching for object recognition, image registration and content-based image retrieval. This is a feature-based matching, which supposes image representation (object description) in the form of a set of multi-location descriptor vectors. The proposed measure called intersection matching distance eliminates outlies (false or missing feature points) while transformation-invariantly matching two sets of descriptor vectors. A block-subdivision algorithm for time-efficient image matching is also described.

Keywords

content-based retrieval; image matching; image registration; image representation; image retrieval; object recognition; content based image retrieval; descriptor vectors; feature based image matching; image registration; image representation; object recognition; outlier resistant dissimilarity measure; Computational complexity; Feature extraction; Image matching; Image retrieval; Object recognition; Robustness; Voltage control; descriptor vector; dissimilarity measure; feature extraction; image matching; intersection matching distance;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition (ICPR), 2010 20th International Conference on

Conference_Location

Istanbul

ISSN

1051-4651

Print_ISBN

978-1-4244-7542-1

Type

conf

DOI

10.1109/ICPR.2010.213

Filename

5596061