A local adaptation of the histogram radon transform descriptor: an application to a shoe print dataset

Authors:
Makoto Hasegawa;Salvatore Tabbone
Affiliations:
Université de Lorraine-LORIA, UMR 7503, Vandoeuvre-lès-Nancy, France;Université de Lorraine-LORIA, UMR 7503, Vandoeuvre-lès-Nancy, France
Venue:
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2012

Citing 3
Cited 0

Symmetric Phase-Only Matched Filtering of Fourier-Mellin Transforms for Image Registration and Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints

International Journal of Computer Vision
Approximate graph edit distance computation by means of bipartite graph matching

Image and Vision Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we propose a shape recognition approach applied to a dataset composed of 512 shoeprints where shapes are strongly occluded. We provide a local adaptation of the HRT (Histogram Radon Transform) descriptor. A shoeprint is decomposed into its connect components and describes locally by the local HRT. Then, following this description, we find the best local matching between the connected components and the similarity between two images is defined as mean of local similarity measures.