Publication Details
Evolutionary Design of Local Binary Pattern Feature Shapes for Object Detection
Fučík Otto, doc. Dr. Ing. (DCSY)
Local Binary Pattern (LBP), AdaBoost, Evolutionary design, feature shapes
This paper deals with the evolutionary design of application specific feature shapes of Local Binary Pattern (LBP) features for object detection in image processing applications. LBP features are very often utilized in image classification systems which are used for pattern recognition. By using genetic algorithm the application of specific weak classifiers' feature shapes, which are highly optimized to achieve a better accuracy of the AdaBoost strong classifier, are being evolved.
This paper deals with the evolutionary design of application specific feature shapes of Local Binary Pattern (LBP) features for object detection in image processing applications. LBP features are very often utilized in image classification systems which are used for pattern recognition. By using genetic algorithm the application of specific weak classifiers' feature shapes, which are highly optimized to achieve a better accuracy of the AdaBoost strong classifier, are being evolved.
@inproceedings{BUT91499,
author="Filip {Kadlček} and Otto {Fučík}",
title="Evolutionary Design of Local Binary Pattern Feature Shapes for Object Detection",
booktitle="2012 NASA/ESA Adaptive Hardware and Systems (AHS-2012) Conference",
year="2012",
series="CFP1263A-USB",
pages="1--8",
publisher="IEEE Computer Society",
address="Nuremberg",
isbn="978-1-4673-1914-0",
url="https://www.fit.vut.cz/research/publication/9987/"
}