What is feature extraction in handwritten character recognition?

What is feature extraction in handwritten character recognition?

Feature extraction is the process of gathering data of different samples so that on the basis of this data we can classify samples with different features. Feature extraction from preprocessed handwritten character plays the most important role in character recognition.

What is feature extraction in image recognition?

Feature extraction is a part of the dimensionality reduction process, in which, an initial set of the raw data is divided and reduced to more manageable groups. These features are easy to process, but still able to describe the actual data set with the accuracy and originality.

What is post processing in OCR?

Optical Character Recognition (OCR) Post Processing involves data cleaning steps for documents that were digitized, such as a book or a newspaper article. One step in this process is the identification and correction of spelling and grammar errors generated due to the flaws in the OCR system.

How is feature extraction used in character recognition?

Feature Extraction In this phase each character is represented as a vector. It extract a set of features. Latter these features will be used to optimised the recognition percentage. General feature extraction methods considers three types of features i. Statistical Fig. 14 Line type normalisation ii.

How are feature vectors used in character recognition?

By problems”, Annals of Eugenics, 7, 179–188 introducing these two extra feature vectors we found the [5] Oivind Due Trier, Anil K Jain, Torfinn Taxt. ―Feature Extraction Methods for Character Recognition-A survey‖, 1995 increase in the accuracy level of the recognition.

Which is a keyword for handwritten character recognition?

Keywords— Handwritten, character, recognition, feature extraction, optical scanner, classification I. INTRODUCTION Handwritten character recognition is a technique of a computer application recognizes handwritten character or sentence from sources such as paper photographs, documents, touchscreens and similar devices by a computer.