Evaluation of Human Perception Thresholds Using Knowledge-Based Pattern Recognition

Abstract

This paper presents research on determining individual perceptual thresholds in cognitive analyses and the understanding of visual patterns. Such techniques are based on the processes of cognitive resonance and can be applied to the division and reconstruction of images using threshold algorithms. The research presented here considers the most important parameters that affect the determination of visual perception thresholds. These parameters are the thematic knowledge and personal expectations that arise at the time of image observation and recognition. The determination of perceptual thresholds has been carried out using visual pattern splitting techniques through threshold methods. The reconstruction of the divided patterns was carried out by combining successive components that, as information was gathered, allowed more and more details to become apparent in the image until the observer could recognize it correctly. The study being carried out in this way made it possible to determine individual perceptual thresholds for dozens of test subjects. The results of the study also showed strong correlations between the determined perceptual thresholds and the participants’ accumulated thematic knowledge, expectations and experiences from a previous recognition of similar image patterns.