DocumentCode
2776393
Title
Is High Resolution Representation More Effective for Content Based Image Classification?
Author
Chen, Liang ; Tokuda, Naoyuki ; Nagai, Akira ; Chen, Xiaoyu
Author_Institution
Northern British Columbia Univ., Prince George
fYear
0
fDate
0-0 0
Firstpage
4045
Lastpage
4050
Abstract
This paper shows by a mathematical model that, for image classification/recognition purposes, high resolution pictures have lower recognition rate than relatively low resolution pictures. The analysis is based on the matching approach by a simple neural network, but we believe that the conclusion remains valid even when the classification process involves complicated matching schemes such as principal component analysis and Gabor transforms.
Keywords
image classification; image matching; image representation; image resolution; neural nets; principal component analysis; transforms; Gabor transform; content based image classification; image matching; image recognition; image representation; image resolution; mathematical model; neural network; principal component analysis; Digital cameras; Face recognition; Humans; Image classification; Image recognition; Image resolution; Mathematical model; Multi-layer neural network; Neural networks; Pixel;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9490-9
Type
conf
DOI
10.1109/IJCNN.2006.246928
Filename
1716656
Link To Document