Optical character recognition using KNN on custom image dataset

The aim is to develop an efficient method which uses a custom image to train the classifier. This OCR extract distinct features from the input image for classifying its contents as characters specifically letters and digits. Input to the system is digital images containing the patterns to be classified. The analysis and recognition of the patterns in images are becoming more complex, yet easy with advances in technological knowledge. Therefore it is proposed to develop sophisticated strategies of pattern analysis to cope with these difficulties. The present work involves application of pattern recognition using KNN to recognize handwritten or printed text.