Artificial visual system and method for image recognition

Abstract

An artificial visual apparatus and method for image recognition having a simple adaptive scaling mechanism enables the definition of scale invariant visual icons in a processing area corresponding to the anterior inferotemporal cortex (AIT) in a one-step, value-based decision making process. Icon related activity states resulting from sensory filtering to a fourth stage KL filter corresponding to the V4 area are recognized independent of the scale and position of the item to be recognized within the maximum visual field. The AIT processing area controls the window of attention in the V4 area and confines further processing onto this selected spotlight. The invention presents a biologically plausible method for scale invariant mapping from the V4 stage filter to the AIT processor. Filtering based on principal component analysis (PCA), or Karhunen-Loeve (KL) filtering, yields image data of the item of interest in the V4 stage filter, such data then being supplied to the AIT processor by a scale-invariant mapping process which controls the number of inputs to the KL filters to achieve constant resolution independent of the scale of the item of interest in the maximum visual field. Thus, the problem of scale-invariant mapping is reduced to a simple adaptive thresholding by feedforward inhibition at the AIT processor.

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