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_aMa. Rhodora F. Pascual and Kristine Bernadette Z. Reyes.
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_aOnline dynamic handwriting recognition /
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_cMa. Rhodora F. Pascual and Kristine Bernadette Z. Reyes.
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_cMarch 2004.46
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_aunmediated
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_aUndergraduate Thesis: (Bachelor of Science in Computer Studies major in Computer Science)- Pamantasan ng Lungsod ng Maynila, 2004.
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_aABSTRACT: This study mainly focuses on the recognition of handwritten characters (numerals, letters, and symbols) into a computer processable format which is commonly known as the Optical character Recognition (OCR). Committing words to paper in handwriting is a uniquely human act, performed daily by millions of people. If you were to present the idea of decoding handwriting to most people, perhaps the first idea to spring to mind would be graphology, which is the analysis of handwriting to determine its authenticity. But the more usual and more frequently overlooked, decoding of handwriting is handwriting recognition-the process of figuring out what words and letters the scribbles and scrawls on the paper represent. A human eye can read the characters of a language written legibly either by a person, or when it is printed. Making the machine do the same, is broadly the problem of :Handwriting Recognition:. This implies endowing the machine with the capability to approximate and thus identify characters correctly, in some sense, a similar capability in human beings. The Online Dynamic Handwriting Recognition is a process of identifying a hand-written character. With the existing algorithm, the proponents encountered several problems> (1) the algorithm only allows drawing a character in one smooth continuous draw. (2) It can only recognize those characters that are pre-defined in its database and (3) it can only recognize single character at a time. A question one may ask when it comes to handwriting recognition is what kind of magic is a computer to become a competent handwriting recognizer? The process involves (1) the image pre-processing (2) the character segmentation process and (3) the identification and classification process. The most difficult to understand in handwriting recognition is mainly in the process of segmentation of the characters, which refers to the extraction of the writing from the handwriting. These writing units would by then used in the recognition process. Especially with handwritten characters, it would take much effort to segment the characters properly because character features cannot be limited into finite parameters.
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