On-line Isolated Handwritten Character Recognition

Author : Zafar, Muhammad Faisal; Mohamad, Dzulkifli; Haq, Ikramul;

On-line handwritten scripts are usually dealt with pen tip traces from pen-down to pen-up positions. Time evaluation of the pen coordinates is also considered along with trajectory information. However, the data obtained needs a lot of preprocessing including filtering, smoothing, slant removing and size normalization before recognition process. Instead of doing such lengthy preprocessing, this paper presents a simple approach to extract the useful character information. The handwritten character is grabbed by its extreme coordinates from left /right and top/bottom and a grid, with specific rows and columns, is drawn which covers the whole character. The algorithm automatically adjusts the size of the grid and its constituents according to the dimensions of the character. Then it searches the presence of character pixels in every box of the grid. The boxes found with character pixels are considered “on” and the rest are marked “off”. A binary string of each character is formed locating the “on” and “off” boxes (named as character digitization) and presented to the counter propagation neural network (CPN) input for training and recognition purposes. The whole process requires no preprocessing and size normalization. The method is applicable for off-line character recognition as well. The technique is tested for upper-case English alphabets for a number of different styles from different peoples. The preliminary results are very encouraging

Keyword : On-line character recognition, character digitization, counter propagation neural networks, extreme coordinates

Sumber : http://repository.petra.ac.id/86/

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