DocumentCode :
3353387
Title :
A rotation and scale invariant descriptor for shape recognition
Author :
Di Lillo, Antonella ; Motta, Giovanni ; Storer, James A.
Author_Institution :
Comput. Sci. Dept., Brandeis Univ., Waltham, MA, USA
fYear :
2010
fDate :
26-29 Sept. 2010
Firstpage :
257
Lastpage :
260
Abstract :
We address the problem of retrieving the silhouettes of objects from a database of shapes with a translation and rotation invariant feature extractor. We retrieve silhouettes by using a “soft” classification based on the Euclidean distance. Experiments show significant gains in retrieval accuracy over the existing literature. This work extends the use of our previously employed feature extractor and shows that the same descriptor can be used for both texture and shape recognition.
Keywords :
feature extraction; image classification; image retrieval; image texture; Euclidean distance; rotation invariant feature extractor; scale invariant descriptor; shape recognition; silhouette retrieval; soft classification; texture recognition; Classification algorithms; Databases; Feature extraction; Robustness; Shape; Transform coding; Visualization; Shape; invariants; object recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1522-4880
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2010.5652671
Filename :
5652671
Link To Document :
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