文件名称:refpaper6_hcrnumkannada
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Abstract. This paper describes a system for isolated Kannada handwritten
numerals recognition using image fusion method. Several digital
images corresponding to each handwritten numeral are fused to generate
patterns, which are stored in 8x8 matrices, irrespective of the size of images.
The numerals to be recognized are matched using nearest neighbor
classifier with each pattern and the best match pattern is considered as
the recognized numeral.The experimental results show accuracy of 96.2
for 500 images, representing the portion of trained data, with the system
being trained for 1000 images. The recognition result of 91 was
obtained for 250 test numerals other than the trained images. Further to
test the performance of the proposed scheme 4-fold cross validation has
been carried out yielding an accuracy of 89 -Abstract. This paper describes a system for isolated Kannada handwritten
numerals recognition using image fusion method. Several digital
images corresponding to each handwritten numeral are fused to generate
patterns, which are stored in 8x8 matrices, irrespective of the size of images.
The numerals to be recognized are matched using nearest neighbor
classifier with each pattern and the best match pattern is considered as
the recognized numeral.The experimental results show accuracy of 96.2
for 500 images, representing the portion of trained data, with the system
being trained for 1000 images. The recognition result of 91 was
obtained for 250 test numerals other than the trained images. Further to
test the performance of the proposed scheme 4-fold cross validation has
been carried out yielding an accuracy of 89
numerals recognition using image fusion method. Several digital
images corresponding to each handwritten numeral are fused to generate
patterns, which are stored in 8x8 matrices, irrespective of the size of images.
The numerals to be recognized are matched using nearest neighbor
classifier with each pattern and the best match pattern is considered as
the recognized numeral.The experimental results show accuracy of 96.2
for 500 images, representing the portion of trained data, with the system
being trained for 1000 images. The recognition result of 91 was
obtained for 250 test numerals other than the trained images. Further to
test the performance of the proposed scheme 4-fold cross validation has
been carried out yielding an accuracy of 89 -Abstract. This paper describes a system for isolated Kannada handwritten
numerals recognition using image fusion method. Several digital
images corresponding to each handwritten numeral are fused to generate
patterns, which are stored in 8x8 matrices, irrespective of the size of images.
The numerals to be recognized are matched using nearest neighbor
classifier with each pattern and the best match pattern is considered as
the recognized numeral.The experimental results show accuracy of 96.2
for 500 images, representing the portion of trained data, with the system
being trained for 1000 images. The recognition result of 91 was
obtained for 250 test numerals other than the trained images. Further to
test the performance of the proposed scheme 4-fold cross validation has
been carried out yielding an accuracy of 89
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