Vision Location Algorithm of Circular Hole in Distributed Clutter Background Using LVQ Network

In view of the traditional way of transportation of oil, where loading process is to apply manpower to guide the large crane tube for perfusion, it is possible of accidents occurred caused by inaccurate opening of the oil tank location and low work efficiency. In order to accurately locate the opening of the oil tank, this study presented a vision location algorithm of the circular hole based on Learning Vector Quantization (LVQ) neural network. In this algorithm, the eccentricity, compactness and other characteristic values of closed curves, which from the image of opening of the oil tank after image pretreatment process, was extracted and these values as the input for the target recognition system based on LVQ neural network that has been trained. And then some input characteristic values are selected to train the LVQ neural network to achieve the learning and prediction purpose. The simulation results show that, the proposed method can be used for the opening of oil tank locating.