Vision Based Fingertip Input System by Recognizing Mandarin Phonetic Symbol Combinations

碩士 === 國立中央大學 === 資訊工程研究所 === 99 === This paper proposes a vision-based handwritten Mandarin phonetic symbols 1(MPS1, Bopomofo) combinations recognition system. This system uses web camera as the input device to detect the trajectory of user’s fingertip in order to recognize user’s handwritten Manda...

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Main Authors: Qun-Jing Shen, 沈群景
Other Authors: HSU-YUNG CHENG
Format: Others
Language:zh-TW
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/79238618527413016973
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spelling ndltd-TW-099NCU053920472017-07-13T04:20:33Z http://ndltd.ncl.edu.tw/handle/79238618527413016973 Vision Based Fingertip Input System by Recognizing Mandarin Phonetic Symbol Combinations 基於視覺的手寫軌跡注音符號組合辨識系統 Qun-Jing Shen 沈群景 碩士 國立中央大學 資訊工程研究所 99 This paper proposes a vision-based handwritten Mandarin phonetic symbols 1(MPS1, Bopomofo) combinations recognition system. This system uses web camera as the input device to detect the trajectory of user’s fingertip in order to recognize user’s handwritten Mandarin phonetic symbols combinations. First, the system locates the fingertip by considering the farthest point from center of palm and records every frame to form the fingertip trajectory. Second, we remove partial entering strokes and leaving strokes by using a bounding box which we propose in this paper. Afterwards, the preprocessed trajectory is encoded by 8-chain codes. Then we remove the rest of entering strokes, leaving strokes, and jitter strokes, and find the turning point of 8-chain codes. Third, we extract features to classify the number of MPS1 combinations by using a Naive Bayes classifier. Afterwards, we separate the MPS1 combinations into single MPS1 symbols and use Hidden Markov models (HMM) to recognize each single MPS1 symbol in the combinations. Finally, we combine the above HMM results with the Naive Bayes classifier’s result to recognize these MPS1symbol combinations. HSU-YUNG CHENG 鄭旭詠 2011 學位論文 ; thesis 54 zh-TW
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language zh-TW
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sources NDLTD
description 碩士 === 國立中央大學 === 資訊工程研究所 === 99 === This paper proposes a vision-based handwritten Mandarin phonetic symbols 1(MPS1, Bopomofo) combinations recognition system. This system uses web camera as the input device to detect the trajectory of user’s fingertip in order to recognize user’s handwritten Mandarin phonetic symbols combinations. First, the system locates the fingertip by considering the farthest point from center of palm and records every frame to form the fingertip trajectory. Second, we remove partial entering strokes and leaving strokes by using a bounding box which we propose in this paper. Afterwards, the preprocessed trajectory is encoded by 8-chain codes. Then we remove the rest of entering strokes, leaving strokes, and jitter strokes, and find the turning point of 8-chain codes. Third, we extract features to classify the number of MPS1 combinations by using a Naive Bayes classifier. Afterwards, we separate the MPS1 combinations into single MPS1 symbols and use Hidden Markov models (HMM) to recognize each single MPS1 symbol in the combinations. Finally, we combine the above HMM results with the Naive Bayes classifier’s result to recognize these MPS1symbol combinations.
author2 HSU-YUNG CHENG
author_facet HSU-YUNG CHENG
Qun-Jing Shen
沈群景
author Qun-Jing Shen
沈群景
spellingShingle Qun-Jing Shen
沈群景
Vision Based Fingertip Input System by Recognizing Mandarin Phonetic Symbol Combinations
author_sort Qun-Jing Shen
title Vision Based Fingertip Input System by Recognizing Mandarin Phonetic Symbol Combinations
title_short Vision Based Fingertip Input System by Recognizing Mandarin Phonetic Symbol Combinations
title_full Vision Based Fingertip Input System by Recognizing Mandarin Phonetic Symbol Combinations
title_fullStr Vision Based Fingertip Input System by Recognizing Mandarin Phonetic Symbol Combinations
title_full_unstemmed Vision Based Fingertip Input System by Recognizing Mandarin Phonetic Symbol Combinations
title_sort vision based fingertip input system by recognizing mandarin phonetic symbol combinations
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/79238618527413016973
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