A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Texture Features for Browsing and Retrieval of Image Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Spectral Algorithm for Seriation and the Consecutive Ones Problem
SIAM Journal on Computing
The String-to-String Correction Problem
Journal of the ACM (JACM)
Computation of Normalized Edit Distance and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Computation of Normalized Edit Distances
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of Interest Points for Image Indexation
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Object-based queries using color points of interest
CBAIVL '01 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'01)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph matching using spectral seriation and string edit distance
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
A Bag of Strings Representation for Image Categorization
Journal of Mathematical Imaging and Vision
Image classification using marginalized kernels for graphs
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
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This paper shows how strings can be used in a natural images classification task. We propose to build an attributed string from a set of regions of interest detected thanks to an interest point detector. These salient zones are characterized by local signatures describing singularities and they are linked by using graph seriation algorithms and perceptual methods. Once each image is represented by a string of signatures, we propose to use string-based edit distances and an ordered histograms-based distance in order to perform the classification task. Experiments have shown that whereas seriation algorithms give approximately the same results, the ordered histogram based distance is more efficient for the considered application.