DocumentCode
2778789
Title
Object Recognition using image descriptors
Author
Mohan, V. ; Shanmugapriya, P. ; Venkataramani, Y.
Author_Institution
Saranathan Coll. of Eng., Trichy
fYear
2008
fDate
18-20 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
Patten recognition techniques are often an important component of intelligent systems to describe, classify and recognise the objects. Object recognition using linear vector quantization neural network which is trained using descriptors such as boundary and regional descriptors is presented in this paper. Out of the various descriptors available, a combination of these descriptors extracted from the input patterns is proposed for recognizing objects using a vector quantization neural network. The feature vector obtained from the object is the combination of a boundary descriptor, the signature or and a regional descriptor, the Zernike moment magnitudes of the image. The results of the testing phase are included at the end of this paper.
Keywords
Zernike polynomials; feature extraction; image classification; learning (artificial intelligence); neural nets; object recognition; quantisation (signal); Zernike moment magnitude; boundary descriptor; feature extraction; image descriptor; intelligent system; linear vector quantization neural network training; object classification; object recognition; patten recognition; regional descriptor; signature descriptor; Data mining; Educational institutions; Feature extraction; Image recognition; Neural networks; Object recognition; Pattern classification; Pattern recognition; Testing; Vector quantization; Classification; Descriptors; Object Recognition; Signature; Zernike Moment;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Communication and Networking, 2008. ICCCn 2008. International Conference on
Conference_Location
St. Thomas, VI
Print_ISBN
978-1-4244-3594-4
Electronic_ISBN
978-1-4244-3595-1
Type
conf
DOI
10.1109/ICCCNET.2008.4787717
Filename
4787717
Link To Document