Digital Recognition And Its Application

Digital recognition has the extensively applied foreground. In this paper, we introduce the actual background and the theory meaning and the research work on digital recognition, we introduce two typical algorithms for digital recognition: the recognition algorithm based on BP neural network and the recognition algorithm based on structure characteristic, we discuss the main application on printed digital recognition and handwriting digital recognition.A specific applied example is discussed for printed digital recognition: digital recognition for the scanned contour drawing. And we put forward a method that can extract the numbers in the drawing efficiently and further recognize these numbers. It includes a great deal of numeral notes in the contour drawing, extracting correctly and recognizing these numbers is an important part in the drawing vector processing. In this paper, we present an advanced method of template matching to extract and recognize the numbers, and then we use the feature extraction method to further recognize different numbers. Experiments show that the speed of the algorithm is quick and the accuracy is high and it has certain anti-interference. A specific applied example is raised for handwriting digital recognition: digital recognition in student's report card. We introduce the basic principle and methods for the handwriting digital extracting and recognition. And we realize the main function of handwriting digital recognition system using the MATLAB. We extract the numbers in the report card using the function of MATLAB, then we select the structure characteristic and the stroke characteristic of the numbers and we present the method of template matching to attain the purpose of recognizing numbers, experiments show that the method based on structure model and knowledge bases is viable for the normative handwriting digital, it also can recognize free handwriting digital under certain condition. In order to enhance recognition rate and reliability, in addition to strengthen the ability of filtering, we still need to enlarge the knowledge base, these all need our further research.