Industrial computer vision using undefined feature extraction

Authors

Phil Evans, University of Wollongong
John A. Fulcher, University of WollongongFollow
Philip Ogunbona, University of WollongongFollow

RIS ID

65872

Publication Details

Evans, P., Fulcher, J. A. & Ogunbona, P. (1995). Industrial computer vision using undefined feature extraction. IEEE International Conference on Neural Networks - Conference Proceedings: Vol 2 (pp. 1145-1149).

Abstract

This paper presents an application of computer The implementation and operation of the system is vision in a real-world uncontrolled environment found at BHP Steel Port Kembla. The task is visual identification of torpedo ladles at a Blast Furnace wlahdilceh. is achieved by reading numbers attached to each 3. IMPLEMENTATION Number recognition is achieved through use of feature extraction using a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN). The novelty in the method used in this application is that the features the MLP is being trained to extract are undefined before the MLP is initialised. The results of the MLP processing are passed to a decision tree for analysis and final classification of each object within the image. This technique is achieving a recognition rate on previously unseen images of greater than 80%