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This paper presents an efficient online handwritten character recognition system for Malayalam characters (OHR-M) using Kohonen network. It would help in recognizing Malayalam text entered using pen-like devices. It will be more natural and efficient way for users to enter text using a pen than keyboard and mouse. To identify the difference between similar characters in Malayalam a novel feature extraction...
Research in the field of character recognition for Urdu script faces challenges mainly due to its characteristics, like cursive nature, multiple fonts and context dependent shapes of characters and their position with respect to the base line. This paper addresses problems recognizing Nasakh script of Urdu Language. The proposed system takes segmented character as input and recognizes them in two...
The difficulties in segmenting cursive words into individual characters have shifted the focus of handwriting recognition research from segmentation-based approaches to segmentation-free (holistic) methods. However, maintaining and training large number of prototypes (models) that represent the words in the dictionary make the training process extremely expensive and difficult in computing resources...
In this paper, a micro inertial measurement unit (muIMU) based on micro electro mechanical systems (MEMS) sensors is applied to sense the motion information produced by characters written by human subjects. The muIMU is built to record the three-dimensional accelerations and angular velocities of the motions during hand-writing. (Here we write the characters in a plane, so only two accelerations and...
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