Biometrics and Bioinformatics

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Shape Matching and Hand Written Digit Identification Using Minkowski Distance


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1 Tamilnadu College of Engineering, Coimbatore, India
     

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Hand written digit recognition is challenging problem in real world application. The digits can be identified by its shape. The shape of the digit from the image is taken as the feature. The shape matching can be achieved by the distance between the reference and test shape. The distance is considered as the error between the test and error shape. By using this error, the images are classified into the digits. The normal NN-classifier is used in our system. Our proposed method is applied to MNIST hand written digit database. The algorithm developed using MATLAB and results were obtained.

Keywords

Digit Recognition, MNIST Data Base.
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Abstract Views: 253

PDF Views: 3




  • Shape Matching and Hand Written Digit Identification Using Minkowski Distance

Abstract Views: 253  |  PDF Views: 3

Authors

K. Senthil Kumar
Tamilnadu College of Engineering, Coimbatore, India
S. Elavarasan
Tamilnadu College of Engineering, Coimbatore, India

Abstract


Hand written digit recognition is challenging problem in real world application. The digits can be identified by its shape. The shape of the digit from the image is taken as the feature. The shape matching can be achieved by the distance between the reference and test shape. The distance is considered as the error between the test and error shape. By using this error, the images are classified into the digits. The normal NN-classifier is used in our system. Our proposed method is applied to MNIST hand written digit database. The algorithm developed using MATLAB and results were obtained.

Keywords


Digit Recognition, MNIST Data Base.

References