An Effect of Ridgelet Transform on Various Distance Measure Techniques in Handwritten Character Recognition

Y.C. Kiran*, V.N. Manjunath Aradhya**, C. Naveena***
* Associate Professor, Department of Information Science and Engineering, Dayanada Sagar College of Engineering, Bengaluru, India
** Associate Professor, Department of MCA, S. J. College of Engineering, Mysuru, India.
*** Professor, Department of Computer Science and Engineering, HKBK College of Engineering, Bengaluru, India.
Periodicity:December - February'2015


The Ridgelet Transform [6] was introduced as a sparse expansion for functions of continuous spaces that are smooth away from discontinuities along lines. The powerful properties of the ridgelets are catching and representing monodimensional singularities in bi-dimensional space [8]. Using these effective properties, in this paper the authors propose an effect of Ridgelet Transform on various Similarity/Distance Measure Techniques namely Euclidean Distance, Modified Squared Euclidean Distance, Correlation Distance and Angle Distance for an unconstrained bi-lingual handwritten character recognition. Ridgelet Transform is used to extract a character image of low pass energy and is then fed to PCA for feature extraction. We conducted experiment on very large database of bi-lingual handwritten characters (Kannada and English). The database contains the samples of 22,600 and the effect of the proposed method is compared with the standard PCA & FLD methods. Among the above mentioned similarity/distance measure techniques the better recognition accuracy were achieved using angle distance measure.


Hand Written Characters, Ridgelets, Distance Measure, Principal Component Analysis.

How to Cite this Article?

Kiran, Y. C., Aradhya, V. N. M., and Naveena, C. (2015). An Effect of Ridgelet Transform on Various Distance Measure Techniques in Handwritten Character Recognition. i-manager’s Journal on Pattern Recognition, 1(4), 11-20.


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