Handwriting recognition has been an issue of concern for many researchers and analysts throughout the previous few decades. Different applications need solution to recognize the cursive nature of handwritten text. The stated nature of written styles needs to implement. To build an efficient working OCR the main drawback is to preprocess noisy document, segment the word, character and then recognize the written text. This paper comprises the needs, relevant research towards handwritten recognition and how to process. We line-out the steps and stages used in the recognition of Kannada handwritten words. The main aim of proposed work is to identify Kannada handwritten answer written in answer booklet and to solve recognition problem by using machine learning algorithms. System provides a detailed concept on pre-processing, segmentation, classifier used to develop systematic OCR tool. The achieved accuracy is of 90% for Kannada handwritten words.