Grzegorzek, Marcin, Sav, Sorin Vasile, Izquierdo, Ebroul ORCID: 0000-0002-7142-3970 and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 (2009) Local wavelet features for statistical object classification and localisation. IEEE Multimedia, 17 (1). p. 118. ISSN 1070-986X
Abstract
This article presents a system for texture-based
probabilistic classification and localisation of 3D objects in 2D digital images and discusses selected applications. The objects are described by local feature vectors computed using the wavelet transform. In the training phase, object features are statistically modelled as normal density functions. In the recognition phase, a maximisation algorithm compares the learned density functions
with the feature vectors extracted from a real scene and yields the classes and poses of objects found in it. Experiments carried out on a real dataset of over 40000 images demonstrate the robustness of the system in terms of classification and localisation accuracy. Finally, two important application scenarios are discussed, namely classification of museum artefacts and classification of
metallography images.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Subjects: | Computer Science > Image processing Computer Science > Information retrieval |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering Research Institutes and Centres > Centre for Digital Video Processing (CDVP) |
Publisher: | IEEE Computer Society |
Official URL: | http://dx.doi.org/10.1109/MMUL.2009.67 |
Copyright Information: | © 2009 IEEE |
Funders: | EU FP6 Network of Excellence - K-Space |
ID Code: | 2338 |
Deposited On: | 06 Apr 2010 15:02 by Noel O'Connor . Last Modified 05 Jan 2022 16:14 |
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