Off-Line Jawi Handwriting Recognition using Hamming Classification
This study 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 can trace bit changes in the two sequence of binary and the bit value distinction will be used to recognize the character.
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