Intelligent adaptive object recognition

Almazmome, Safa and Zhang, Li (2016) Intelligent adaptive object recognition. In: 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, Piscataway, pp. 2272-2276. ISBN 978-1-5090-4094-0

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Abstract

This research proposes an object recognition system using image processing and neural network based classification. The system is capable of recognizing 7 objects from an uncluttered background by extracting color, texture and shape features. The proposed system consists of image segmentation, feature extraction and classification. Diverse neural network topology settings have been employed for evaluation. Experimental results indicate that the proposed system achieves high accuracy 98% accurate for real-time object recognition tasks.

Item Type:	Book Section
Uncontrolled Keywords:	computer vision and image processing, Object recognition, neural networks
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Becky Skoyles
Date Deposited:	09 Dec 2016 14:20
Last Modified:	12 Oct 2019 22:26
URI:	http://nrl.northumbria.ac.uk/id/eprint/28848

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