Title :
Similarity-based image retrieval from plural key images by self-organizing map with refractoriness
Author :
Tanirnizu, H. ; Osana, Yuko
Author_Institution :
Tokyo Univ. of Technol., Tokyo
Abstract :
In this research, we propose a similarity-based image retrieval from plural key images by self-organizing map with refractoriness. In the self-organizing map with refractoriness, the plural neurons in the map layer corresponding to the input can fire sequentially because of the refractoriness. The proposed image retrieval system from plural key images using the self-organizing map with refractoriness makes use of this property in order to retrieve plural similar images. In this image retrieval system, as the image feature, not only color information but also spectrum, impression words and keywords are employed. In the proposed system, the similarity-based image retrieval from plural key images can be realized. We carried out a series of computer experiments and confirmed that the effectiveness of the proposed system.
Keywords :
image retrieval; self-organising feature maps; image feature; map layer; plural key images; self-organizing map; similarity-based image retrieval; Artificial neural networks; Associative memory; Biological neural networks; Brain modeling; Chaos; Fires; Image retrieval; Information processing; Information retrieval; Neurons;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4633890