• Akshay Sanjay mane
• Kiran b ingle
• Vishwajeet swami

Handwritten digit and letter recognition is a very important topic in the field of image processing and pattern recognition. Handwritten digit and letter recognition poses different problem because of different writing styles, similarity in structure and angle of orientation. Therefore, it is very important to find effective method for recognition and classification of digit and letter. Handwritten digit and letter recognition have various applications such as number plate recognition, extracting business card information, bank check processing, postal address processing, passport processing, signature processing etc. This paper proposes a method of handwritten digit and letter recognition using OCR, support vector machine (SVM) classifiers for classification standard sci kit learn dataset for SVM and standard template dataset for OCR is used. input image is binarized and later stray pixels are removed. the proposed method was able to obtain highest accuracy for SVM classifier.

OCR; Skit learn;SVM;MATPLOTLIB

"Handwritten character recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.378-381, March-2019, Available :http://www.jetir.org/papers/JETIR1903F57.pdf

"Handwritten character recognition", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp378-381, March-2019, Available at : http://www.jetir.org/papers/JETIR1903F57.pdf