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An on-line interactive self-adaptive image classification framework

Sannen, Davy; Nuttin, Marnix; Smith, Jim; Tahir, Muhammad Atif; Caleb-Solly, Praminda; Lughofer, Edwin; Eitzinger, Christian

Authors

Davy Sannen

Marnix Nuttin

Profile Image

Jim Smith James.Smith@uwe.ac.uk
Professor in Interactive Artificial Intelligence

Muhammad Atif Tahir

Praminda Caleb-Solly

Edwin Lughofer

Christian Eitzinger



Contributors

Antonios Gasteratos
Editor

Markus Vincze
Editor

John K. Tsotsos
Editor

Abstract

In this paper we present a novel image classification framework, which is able to automatically re-configure and adapt its feature-driven classifiers and improve its performance based on user interaction during on-line processing mode. Special emphasis is placed on the generic applicability of the framework to arbitrary surface inspection systems. The basic components of the framework include: recognition of regions of interest (objects), adaptive feature extraction, dealing with hierarchical information in classification, initial batch training with redundancy deletion and feature selection components, on-line adaptation and refinement of the classifiers based on operators' feedback, and resolving contradictory inputs from several operators by ensembling outputs from different individual classifiers. The paper presents an outline on each of these components and concludes with a thorough discussion of basic and improved off-line and on-line classification results for artificial data sets and real-world images recorded during a CD imprint production process. © 2008 Springer-Verlag Berlin Heidelberg.

Citation

Sannen, D., Nuttin, M., Smith, J., Tahir, M. A., Caleb-Solly, P., Lughofer, E., & Eitzinger, C. (2008). An on-line interactive self-adaptive image classification framework. Lecture Notes in Artificial Intelligence, 5008 LNCS, 171-180. https://doi.org/10.1007/978-3-540-79547-6_17

Journal Article Type Conference Paper
Publication Date Jun 9, 2008
Journal Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer Verlag
Peer Reviewed Not Peer Reviewed
Volume 5008 LNCS
Pages 171-180
ISBN ;
DOI https://doi.org/10.1007/978-3-540-79547-6_17
Keywords image classification, feature extraction, on-line adaptation and evolution, resolving contradictory inputs, classifier ensembles
Public URL https://uwe-repository.worktribe.com/output/1021638
Publisher URL http://dx.doi.org/10.1007/978-3-540-79547-6_17