An Analytical Study Of Handwritten Character Recognition

Handwritten Character Recognition is a crucial part of Optical Character Recognition (OCR) through which the computer understands the handwriting of individuals automatically from the image of a handwritten script. From a decade, OCR becomes the most important application of Pattern Recognition, Machine Vision and Signal Processing for the rapid growth of technology, which can be described as the Electronic or Mechanical conversion of the captured or scanned image. The image is converted into the machine encoded form that can be further used in machine translation, text to speech conversion, text mining and the storage of data. Selections of appropriate feature extraction and classification methods are the crucial factors for achieving a higher rate of recognition with greater level of accuracy for handwritten characters to accurately achieve recognition of each and every letter. Here, in this paper the authors attempt to give a more elaborative image for a comprehensive review that has been proposed to achieve a deep study of the handwritten characters recognition, and this data will be useful for the readers working in the field of handwritten character recognition.