ABSTRACT
The process of automatically identifying alphabets and digits using a computer or other equipment is known as handwritten alphabets and digits recognition. It’s utilised in a number of industries, including banking, the postal service, and other areas where handwritten names must be recognised. This paper uses database for using alphabets and digits as samples, employs various algorithms like KNN, SVM, BPNN, CNN and deep learning for handwritten alphabets and digits recognition. Here recognition rate and recognition accuracy of the five different algorithms are compared and analysed. Among the five different algorithms, the ANN algorithm produces best result.
