Research of image recognition method based on reading cognitive model

This paper simulates the human being's cognitive mechanism of pattern recognition. Based on the reading cognition model, a feature extraction method is proposed to calculate the image features from the visual information point of view. A universal pattern recognition framework is constructed through the modeling of the topological relationship of primitives. A sliding window approach is applied to simulate the human pattern cognition mechanism. The sliding process is used to extract the local structure features and assemble the topological relationship at the meantime. In this paper, the recognition model is a hybrid of the predictive artificial neural network ANN and the hidden markov model HMM. ANNs are used to model the primitives of the patterns depending on their supper computing ability, and the HMM is used to model the pattern's overall topological structure according to its strong ability of time series data processing. The experimental results verified the effectiveness and versatility of the proposed method.