Computational Model for Image Processing in the Minds of People with Visual Agnosia using Fuzzy Cognitive Map

The Agnosia is a neurological condition that leads to an inability to name, recognize, and extract meaning from the visual, auditory, and sensory environment, despite the fact that the receptor organ is perfect. Visual agnosia is the most common type of this disorder. People with agnosia have trouble communicating between the mind and the brain. As a result, they cannot understand the images seen. In this paper, a model is proposed that is based on the visual pathway so that it first receives the visual stimulus and then, after understanding, the object is identified. In this paper, a model based on the visual pathway is proposed and using intelligent Fuzzy Cognitive Map will help improve image processing in the minds of these patients. First, the proposed model that is inspired by the visual perception pathway, is designed. Then, appropriate attributes that include the texture and color of the images are extracted and the concept of the seen image is perceived using Fuzzy Cognitive Mapping, the meaning recognition and the relationships between objects. This model reduces the difficulty of perceiving and recognizing objects in patients with visual agnosia. The results show that the proposed model, with 98.1% accuracy, shows better performance than other methods.