DocumentCode
2498252
Title
An image recognition based on neural oscillator network
Author
Hoshino, Kenta ; Igarashi, Hajime
Author_Institution
Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo, Japan
fYear
2010
fDate
18-23 July 2010
Firstpage
1
Lastpage
6
Abstract
This paper introduces a novel image recognition method based on the neural oscillator network. In the present method, the dynamics of neurons is determined from neural coupling strengths relevant to the similarities in pixel levels, which have been used in the conventional image segmentation, as well as geometrical local features obtained from the Gabor filtering. Then the image regions under resultant neural synchronization are identified. It is shown that the accuracy of the present method, applied to the image recognition for pairs of identical and different alphabetical letters, is 76.9% and 62.2%, respectively. Moreover, the simple polygons are also correctly recognized by the present method.
Keywords
Gabor filters; character recognition; image recognition; image resolution; image segmentation; neural nets; oscillators; Gabor filtering; alphabetical letters; geometrical local features; image recognition; image segmentation; neural coupling strengths; neural oscillator network; neuron dynamics; pixel levels; resultant neural synchronization; Image segmentation; Oscillators; Pixel; Synchronization;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location
Barcelona
ISSN
1098-7576
Print_ISBN
978-1-4244-6916-1
Type
conf
DOI
10.1109/IJCNN.2010.5596947
Filename
5596947
Link To Document