An intelligent scanner with handwritten odia character recognition capability

Character recognition plays an important role in the modern world. It can solve more complex problems and make human´s job easier. Difficulties in recognition of handwritten text in Indian scripts include extreme cursiveness in their handwritten form due to the presence of vowel modifiers and compound characters. Here we propose a simple yet robust structural solution for recognizing handwritten characters in Odia (the official language of Odisha, a state in Republic of India). In the proposed system, a given text is segmented into lines and then each line is segmented into individual words and then each word is segmented into individual characters or basic symbols. Basic symbols are identified as the fundamental units of segmentation used for recognition. All the characters are divided into two groups (Group-I and Group-II) according to the property i.e. whether a vertical line is present or absent at the right-most part. All the characters of the two groups are resized into 20×14 pixels, which are directly subjected to train the two neural networks (one for Group-I and another for Group-II). Using the proposed system we have found better result for proper recognition rate as compared to other methods. The proposed sensing system is also found to be efficient in compressing the script data quite efficiently.