PENGENALAN AKSARA BALI DENGAN PENDEKATAN METODE DIRECTION FEATURE DAN AREA BINARY OBJECT FEATURE - Ni Made Ari Pratiwi; Widi Hapsari; Theresia Herlina R. (Universitas Kristen Duta Wacana, 2013)
The rise of technology has been contributing advances to science, and to human being in making jobs far much easier to do, including pattern recognition. This research focused on character recognition by developing a system capable to recognise images of printed Balinese traditional character, which has a distinct feature of having perceptually similar characters, where each others are often differentiated only by a small stroke or a curve. The system itself took several processes to recognise a character. First, the image containing Balinese characters is preprocessed. Afterwards, two object features are extracted from the image: Direction and Binary Object Area. Both features then tested for similarity using Euclidean distance with the same features already obtained from the control images. From 573 characters tested to the system, 559 are recognized as characters and 526 are correctly recognized as the right character, which yields an overall accuracy of 91.8%. Recognition results are dependent to character spacing condition.