Performance Comparison of Feature Extraction Methods for Neural Network Based Object Recognition
نویسندگان
چکیده
Preprocessing and feature extraction can significantly enhance the performance of a neural network based classifier. In this paper several feature extraction techniques including edge filters, local features and distance transformation are selected for image preprocessing in order to improve the recognition accuracy in combination with a neural network classifier. The visual object recognition performance of these algorithms is extensively compared based on a real world data set with significant variation of viewpoint and illumination.
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