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