Visual Keyword Image Retrieval Based on Synergetic NeuralNetwork for Web-Based Image Search

Authors:
Tong Zhao;Lilian H. Tang;Horace H. S. Ip;Feihu Qi
Affiliations:
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PRC;School of Electronics, Computing and Mathematics, University of Surrey, United Kingdom;Centre for Innovative Applications of Internet and Multimedia Technologies, (AIM tech Centre), City University of Hong Kong, Hong Kong;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200030, PRC
Venue:
Real-Time Systems
Year:
2001

Citing 8
Cited 0

Synergetic computers and cognition: a top-down approach to neural nets

Synergetic computers and cognition: a top-down approach to neural nets
Local Invariants For Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Discriminant Eigenfeatures for Image Retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Image Retrieval by Elastic Matching of User Sketches

IEEE Transactions on Pattern Analysis and Machine Intelligence
Similar-Shape Retrieval In Shape Data Management

Computer
Vector-Space Image Model (VSIM) for Content-Based Retrieval

DEXA '99 Proceedings of the 10th International Workshop on Database & Expert Systems Applications
Image-Based Form Document Retrieval

ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
An FFT-based technique for translation, rotation, and scale-invariant image registration

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Feature extraction and similarity measure are two basickey issues in image retrieval. Combining the advantages of SNNin image recognition and selective attention for image retrieval,a novel visual keywords-driven image retrieval approach basedon these properties has been proposed. By using a predefinedset of visual keywords as prototype patterns stored with theSNN and then measuring the degree of similiarity of the storedimages to the visual keywords, we show that such a visual keyworddriven SNN can provide the framework for image indexing or retrievalwhich is scalable, robust and efficient for web-based search.