Significantly improving scan-based shape representations using rotational key feature points

Authors:
Yasser Ebrahim;Maher Ahmed;Siu-Cheung Chau;Wegdan Abdelsalam
Affiliations:
Wilfrid Laurier University, Waterloo, ON, Canada;Wilfrid Laurier University, Waterloo, ON, Canada;Wilfrid Laurier University, Waterloo, ON, Canada;University of Guelph, Guelph, ON, Canada
Venue:
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Year:
2010

Citing 6
Cited 0

On Aligning Curves

IEEE Transactions on Pattern Analysis and Machine Intelligence
Using Pen-Based Outlines for Object-Based Annotation and Image-Based Queries

VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Efficient contour-based shape representation and matching

MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Using the Inner-Distance for Classification of Articulated Shapes

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Shape representation and description using the Hilbert curve

Pattern Recognition Letters
A multiscale representation method for nonrigid shapes with a single closed contour

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

In a previous paper we have presented the idea of representing the shape of a 2D object by scanning it following a Hilbert curve then performing wavelet smoothing and sampling. We also introduced the idea of using only a subset of the resulting signature for comparison purposes. We called that set the Key Feature Points (KFPs). In this paper we introduce the idea of taking the KFPs over a number of views of the original shape. The proposed improvement results in a significant increase in recognition rates when applied to the MPEG-7 and ETH-80 data sets when the Hilbert scan is used. Similar improvement is achieved when the raster scan is used.