Fuzzy neural network for document region classification using human visual perception features

This paper describes a fuzzy neural network classifier to perform document region classification using features obtained from human visual perception theories. The foundations of the classifier are derived from human visual perception theories. The theories analyzed are texture discrimination based on textons, and perceptual grouping. Based on these theories, the classification task is stated as a texture discrimination problem and is implemented as a preattentive process. Engineering techniques are then developed to extract features for deciding the class of information contained in the regions. The feature derived from the human visual perception theories is a measurement of periodicity of the blobs of the text regions. This feature is used to design a fuzzy neural network classifier. The results of this work may be a good support for the assertion that visual perception theories may be incorporated into engineering techniques to produce better results.