The presentation will describe an algorithm through which one can recognize Devanagari Characters. Devanagari is the script in which Hindi is represented. This algorithm could automatically segment character from the image of Devenagari text and then recognize them. For extracting the individual characters from the image of Devanagari text, algorithm segmented the image several times using the vertical and horizontal projection. The algorithm starts with first segmenting the lines separately from the document by taking horizontal projection and then the line into words by taking vertical projection of the line. Another step which is particular to the separation of Devanagari characters was required and was done by first removing the header line by finding horizontal projection of each word. The characters can then be extracted by vertical projection of the word without the header line. Algorithm uses a Kohonen Neural Netowrk for the recognition task. After the separation of the characters from the image, the image matrix was then downsampled to bring it down to a fixed size so as to make the recognition size independent. The matrix can then be fed as input neurons to the Kohonen Neural Network and the winning neuron is found which identifies the recognized the character. This information in Kohonen Neural Network was stored earlier during the training phase of the neural network. For this, we first assigned random weights from input neurons to output neurons and then for each training set, the winning neuron was calculated by finding the maximum output produced by the neurons. The wights for this winning neuron were then adjusted so that it responds to this pattern more strongly the next time.

1. DEVANAGARI CHARACTER RECOGNITION

27. DEVANAGARI CHARACTER RECOGNITION Thanks.