Technology of Selective Questionnaire Recognition based on Neural Network

In the process of automatic questionnaire recognition and statistic,there always is data misjudgment caused by folding,bending,distorting and contamination of the paper.Considering complexity in manual statistic,it is valuable for developing an intelligent process system with automation and high efficiency.This paper puts forward data process method based on neural network to handle the scanned image of questionnaire,sets up the Hopfield network recognition model based on MATLAB.Then it discusses specifically about three important parts of this procedure,such as image preprocessing,feature extraction,Hopfield network training and recognition.According to the established model,system simulation could get 100% of recognition rate.In real operation,once the sufficient and reliable samples are obtained,recognition rate could reach 96%,so the desired effect are achieved.