<![CDATA[Nowadays, handwriting recognition has been widely used for analyzing signature, reading address as well aschanging text to hypertext. Common steps in handwriting recognition system consist of pre-processing,segmentation, feature extraction, classification and post-processing. This research describes segmentationmethods for handwriting character which acquired using online device. Characters used in this research are 19latin alphabets. In the first step, pre-processing is taken place by removing noise manually. The next step iscalculating the speed of writing. The acquired speed value is further used to calculate acceleration by applyinglow-passfilter. As shown in the figure, it is found that there are many peak change has been identified so thatlow-pass filter is also used to reduce the number of segment. Too many segments may increase the difficulties ofthe next process. This research employs 4 segmentation methods, such as Positive Negative Acceleration,Positive Positive Acceleration, Negative Positive Acceleration and Minimum Speed. From the experiments, it isidentified that by applying minimum speed, character segmentation can be perform quite wellKeyword(s): Segmentation, Character, Speed, Acceleration, Low-pass Filter.Subject Description: I.4 Image Processing and Computer Vision | I.4.6 Segmentation | Edge and featuredetection]]>
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