DocumentCode
3202011
Title
Combining image features for image classification
Author
Baharudin, B. ; Qahwaji, R. ; Jiang, J. ; Rahman, P.
fYear
2007
fDate
25-28 Nov. 2007
Firstpage
268
Lastpage
272
Abstract
In this paper, we use neural networks and support vector machines (SVMpsilas) to compare the classification performances of four proposed image features. Of the four image features, two are developed by the authors, whereas the other two are well-known image features which we included for benchmark purposes. Indirectly the performances of the two image classifiers are compared. Based on the experiments that were carried out, it was found that our proposed combined image features gave the best performance amongst the four image features. In terms of the classifiers, SVM proved to be the better classifier.
Keywords
feature extraction; image classification; learning (artificial intelligence); neural nets; support vector machines; feature extraction; image classification; image features; machine learning; neural networks; support vector machines; Artificial neural networks; Feature extraction; Image classification; Image retrieval; Machine learning; Machine learning algorithms; Neural networks; Shape; Support vector machine classification; Support vector machines; Feature extraction; image classification; machine learning; neural networks; support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4244-1355-3
Electronic_ISBN
978-1-4244-1356-0
Type
conf
DOI
10.1109/ICIAS.2007.4658388
Filename
4658388
Link To Document