DocumentCode
2265410
Title
Classification of planar shapes using multiresolution circular autoregressive models
Author
Das, M. ; Paulik, Mark J. ; Wang, Yung-Da ; Li, Chia Che
Author_Institution
Oakland Univ., Rochester, MI, USA
fYear
1993
fDate
16-18 Aug 1993
Firstpage
994
Abstract
A new multiresolution circular autoregressive (MCAR) shape boundary modeling technique is developed. The circular autoregressive model represents the shape contour sequence at short, medium, and long term boundary correlations. The model is independent of shape size, orientation, and location. The feature weighting (FW) recognition technique is used to classify the shapes. Experimental shape classification results are provided
Keywords
autoregressive processes; computer vision; feature extraction; image classification; boundary correlations; feature weighting recognition technique; multiresolution circular autoregressive models; planar shape classification; shape boundary modeling technique; shape contour sequence; Application software; Computer industry; Computer vision; Electrical equipment industry; Industrial control; Manufacturing industries; Production facilities; Robot vision systems; Shape; Spatial resolution;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1993., Proceedings of the 36th Midwest Symposium on
Conference_Location
Detroit, MI
Print_ISBN
0-7803-1760-2
Type
conf
DOI
10.1109/MWSCAS.1993.343238
Filename
343238
Link To Document