Abstract
In human visual perception, there is an intuitive tolerance (perceptual constancy) for perceiving raw stimulus patterns which may be rotated, scaled, deformed, or noisy to some extent for a learned pattern. Such an intuitive property of perception is a major feature of human pattern recognition, where a recognition mechanism (consider the character recognition for example) may not necessarily follow in a stroke‐based (feature‐oriented) scheme; rather, it may follow in a whole‐image‐based (spatial‐oriented) scheme. In this paper, we present a conceptual development framework for intuitive human pattern recognition. The implementation model is called I‐net and basically consists of three parts: an attention mechanism, a generalization mechanism, and a recognition mechanism. The paper begins with describing the intuitive properties involved in recognizing 2‐D binary patterns, following an introduction to intuitive human pattern recognition. Then the details of the I‐net are described and experimental results are presented. The paper concludes that the proposed framework provides another direction for approaching human pattern recognition.
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