A multiresolution neural network classifier for machine vision

The authors discuss the first subcomponent of a vision system being developed to combine the benefit of the flexible approach offered by using neural networks as classifiers and some traditional image classification techniques which have failed to produce the expected results due to the inadequacies of the classification system hitherto used. By using a multiresolution pyramid to focus the attention of the system on areas that are likely to contain the features being sought, the performance of the system in terms of its accuracy and speed of location is improved. Furthermore, by breaking the problem of locating an object into subgoals, the construction and operation of the detectors is reduced in complexity