02-04-2017, 03:21 PM
I am Sharath I want code to recognize Kannada characters in the vehicle number plate. Because we are doing project on this. So please help me by sending the code for this to ksharada816[at]gmail.com
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source code for recognition of handwritten kannada script using matlab
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I am Sharath I want code to recognize Kannada characters in the vehicle number plate. Because we are doing project on this. So please help me by sending the code for this to ksharada816[at]gmail.com
10-04-2017, 12:24 PM
The task of recognizing manuscript numbers, using a classifier, is of great importance. In this paper the radial base function technique is applied for numerical handwriting recognition of Devanagari Script. Much work has been done in Devanagari numeral recognition using different techniques to increase recognition accuracy. Because the database is not created globally, the database was first created by implementing the preprocess in the training data set. Then, through the use of Principal Component Analysis, we have extracted the characteristics of each image, some researchers have also used the extraction of density characteristics. Since different people have different writing styles, so here we are trying to form a system where numeral recognition becomes easy. Then, in the hidden layer, the centers are determined and weights are determined between the hidden layer and the output layer of each neuron to calculate the output, where output is the value of the adder of each neuron.
![[Image: Figure-1-Devanagari-Numerals.png]](https://www.researchgate.net/profile/Mahesh_Jangid/publication/233380088/figure/fig1/AS:300050812030978@1448549096394/Figure-1-Devanagari-Numerals.png)
Handwriting recognition has existed since 1980. To date, much research has been done. Automatic reading of numeric fields has been attempted in various application areas, such as recognition of online hands on computer tablets, recognition of postal codes in mail for postal sorting, bank check processing, numbers On forms filled in manually (for example) in. In solving this domain of handwriting recognition, many challenges are faced. Since handwritten digits do not always have the same size, thickness or orientation and position in relation to the margins, many handwritten versions are even difficult to recognize.
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