In the field of Optical Character Recognition (OCR), zoning is used to extract topological information from patterns. In this paper we propose Zone based features for recognition of the mixer of Handwritten and Printed Kannada Digits. A digit image is divided into 64 zones and pixel density is computed for each zone. This procedure is sequentially repeated for entire zone. Finally 64 features are extracted for classification and recognition. There could be some zone column/row having empty foreground pixels. Hence the feature value of such particular zone column/row in the feature vector is zero. The KNN and SVM classifiers are used to classify the mixed handwritten and printed Kannada digits. We have obtained 97.32% & 98.30% recognition rate for mixed handwritten and printed Kannada digits by using KNN and SVM classifiers respectively.

1. A.F.R.Rahman, M.C.Fairhurst, “Recognition of handwritten Bengali Characters: A Novel Multistage Approach”, Pattern Recognition, 35,997-1006, 2002.
2. R.Chandrashekaran, M.Chandrasekaran, Gift Siromaney, “Computer Recognition of Tamil, Malayalam and Devanagari characters”, Journal of IETE, Vol.30, No.6, 1984.
3. U.Pal, N.Sharma, F.Kimura, "Recognition of Handwritten Kannada Numerals", 9th International Conference on Information Technology (ICIT'06), ICIT, pp. 133-136.
4. Dinesh Acharya U, N VSubba Reddy and Krishnamurthy, “Isolated handwritten Kannada numeral recognition using structural feature and K-means cluster”, IISN-2007, pp-125 -129.
5. S.V.Rajashekararadhya and P.V.Vanaja Ranjan,”Neural network based handwritten numeral recognition of Kannada and Telugu scripts”, TENCON 2008.
6. Oivind Trier, Anil Jain, Torfiinn Taxt, “A feature extraction method for character recognition-A survey“, pattern Recognition, vol 29, No 4, pp-641-662, 1996.
7. B.V.Dhandra, Mallikarjun Hangarge, Gururaj Mukarambi, ”Spatial Features for Handwritten Kannada and English Character Recognition”, Special Issue on RTIPPR-10, International Journal of Computer Applications, pp.146-150, Aug-2010.
8. M.Hanmandlu, Grover, V. K.Madasu, S.Vasikarla, "Input Fuzzy Modeling for the Recognition of Handwritten Hindi Numerals", International Conference on Information Technology (ITNG'07), 2007.
9. T V Ashwin, P S Sastry: “A Font and Size-Independent OCR System for Printed Kannada Documents using Support Vector Machine.Sadhana, vol. 27, pp.35-38, Feb. 2002.
10. Nagbhushan P, Pai.Radhika “Modified region Decomposition Method and Optimal Depth Decomposition Tree in the Recognition of non–uniform Sized Characters experimentation with Kannada characters”. Pattern Recognition.Letters-20:1467-1475
11. Kunte Sanjeev R, Sudhaker Samuel, “Hu’s invariant moments& Zernike moments approach for the recognition of basic symbols in Printed Kannada text”. Sadhana Vol .32, Part 5, October 2007, pp. 521-533.
12. B.V.Dhandra, Mallikarjun Hangarge, Gururaj Mukarambi, "Spatial Features for Multi-Font/Multi-Size Kannada Numerals Recognition”, International Conference on Communication, Computation, Control and Nano Technology (ICN-2010),Bhalki, Bidar, Karnataka.
13. G.G.Rajput, Rajeswari Horakeri, Sidramappa Chandrakant," Printed and Handwritten Mixed Kannada Numerals Recognition Using SVM", International Journal on Computer Science and Engineering Vol. 02, No. 05, 2010,pp.1622-1626.
14. A.Majumdar and B.B.Chaudhuri," A MLP Classifier for Both Printed and Handwritten Bangla Numeral Recognition", ICVGIP 2006, LNCS-4338, pp.796 – 804, 2006.
15. Rafael C Gonzalez, Richard E Woods and Steven L Eddins, “Digital Image Processing using MATLAB”, Year 2008.

OCR Zone Features KNN SVM