HANDWRITTEN ALPHANUMERIC CHARACTER RECOGNITION AND COMPARISON OF CLASSIFICATION TECHNIQUES
Journal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.7, No. 1)Publication Date: 2018-01-30
Authors : Neha; Deepti Ahlawat;
Page : 419-428
Keywords : HCR; Feature extraction methods; HOG; PCA; Image classification techniques; SVM; KNN; NN.;
Abstract
Several techniques have been proposed by many researchers for handwritten as well as printed character and numerals recognition. Recognition is the process of conversion of handwritten text into machine readable form. To achieve the best accuracy of any recognition system the selection of feature extraction and classification technique is important. The data about the character is collected by the features and accordingly classifiers classify the character uniquely. For handwritten characters there are drawbacks like it differs from one writer to another, even when same person writes same character a number of times there is difference in shape, size and position of character. Latest research in this area have used various types of method, classifiers and features to reduce complexity of recognizing handwritten text. In this paper, advantages and disadvantages of two different techniques of feature extraction and classification have been discussed.
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