Off-Line Jawi Handwriting Recognition using Hamming Classification

Research on character recognition is divided into two forms which are on-line and off-line recognition. For on-line recognition, the user will write on input surface which is called tablet and it will recognize the character immediately, while off-line recognition is a recognition process that using a written document which will be scan and save into a computer for further processing. Pre-processing such as transformation of image into binary, line segmentation or character segmentation need to be done and it must be done accurately as possible. After pre-processing is done, the recognition process will recognize the character that has been segmentized. This research is focusing on off-line character recognition. The algorithm of pre-processing such as line and character segmentation is studied and determined so that the design can give a good result and can be implemented in hardware. A process of transformation towards the characters is done using Discrete Wavelet Transform since it will show the details of the pixels. After that, a process to generate a sequence of binary that using a value of threshold (threshold value is determine by experiment) is done so that it can be use for recognition process. This sequence of binary will be classified using Hamming Distance which it can trace bit changes in the two sequence of binary and the bit value distinction will be used to recognize the character.