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1

林依民 and Yi-min Lin. "Computer recognition of printed Chinese characters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1990. http://hub.hku.hk/bib/B31209919.

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2

梁祥海 and Cheung-hoi Leung. "Computer recognition of handprinted Chinese characters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1986. http://hub.hku.hk/bib/B31230660.

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3

施雷 and Lui Sze. "Computer recognition of printed Chinese characters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31213601.

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4

Leung, Cheung-hoi. "Computer recognition of handprinted Chinese characters /." [Hong Kong : University of Hong Kong], 1986. http://sunzi.lib.hku.hk/hkuto/record.jsp?B12322131.

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5

Lau, Kin-keung. "Preprocessing and postprocessing techniques for improving the performance of a Chinese character recognition system /." [Hong Kong : University of Hong Kong], 1991. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13154345.

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6

Hu, Marie. "A study of Chinese characters recognition methods." Cincinnati, Ohio : University of Cincinnati, 2002. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=ucin1035813506.

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7

Wong, Chi-hung. "Hand-written Chinese character recognition by hidden Markov models and radical partition /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19669380.

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8

Chou, Yu-Ju. "Hemispheric lateralisation in the recognition of Chinese characters." Thesis, University of Edinburgh, 2004. http://hdl.handle.net/1842/24431.

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The central core of this thesis is recognition of Chinese characters, integrated by ten experiments of four main themes. The first theme is hemispheric lateralisation of the length effect in Chinese character recognition. The second theme is to investigate this bilateral effect with Chinese characters presented on both visual fields simultaneously. The outcome confirmed that there was indeed a bilateral advantage found from male Chinese readers. For this group of subjects, the longer the stimuli were, the more bilateral collaboration was found, and the collaboration of bilateral presentation took the least response latency in the lexical decision task than any other unilateral presentation. The third theme of this thesis was to the recognition process, holistic or component, while recognizing Chinese characters. The method was taken from the experiment of Face Illusion (Thompson, 1980, quote from Bruce, V. and Young, A., 1998) in which the eyes of Margaret Thatcher’s portrait were turned upside down and the whole portrait was then inverted again for subjects to recognise. In our own experiment, we replicated the methodology and changed Chinese characters by inverting the phonetic or semantic radicals and then turned the whole character around. The results showed no support for the componential processing hypothesis. The fourth theme of the thesis was a self-collection of errors made by slips of the eyes in reading vertically written Chinese. We presented nine types of reading errors in a chart with examples of each type.
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9

葉賜權 and Chee-kuen Yip. "Machine recognition of multi-font printed Chinese Characters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1990. http://hub.hku.hk/bib/B31210120.

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10

Ren, Manling. "Algorithms for off-line recognition of Chinese characters." Thesis, Nottingham Trent University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.245175.

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11

Al-Emami, Samir Yaseen Safa. "Machine recognition of handwritten and typewritten Arabic characters." Thesis, University of Reading, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359173.

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12

Wang, Jianguo. "Off-line computer recognition of unconstrained handwritten characters." Thesis, The University of Sydney, 2001. https://hdl.handle.net/2123/27805.

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This thesis presents several techniques for improving the performance of off—line Optical Character Recognition (OCR) systems: broken character mending and recognition, feature extraction methods in OCR and hybrid methods for handwritten numeral recognition. As an application, form document image compression and indexing is also introduced. Broken characters mending techniques are investigated first. A macrostrtrcture analysis (MSA) mending method is proposed based on skeleton and boundary information and macrostructure analysis that investigates the stroke tendency and other properties of handwritten characters. A new skeleton end extension algorithm is also introduced. The MSA mending method is combined with a skeleton-based recognition algorithm to verify its efficiency. Experiment results indicate that significant improvement has been achieved. The feature extraction methods in OCR are analyzed by comparing their effectiveness in different situations. Several factors and their relation with the effectiveness of each feather extraction method are investigated. A dynamic feature extraction method is developed to improve the performance of hybrid OCR systems. Hybrid methods for handwritten numeral recognition are then described, which combine two compensatory recognisers by analyzing their performance for several aspects. The different performances of the two algorithms for broken, connected or slanted numerals. and the rneasurement—level decision provided by the neural network algorithm are detected and combined to develop matching rules for each recognition method. Five combination methods are developed to meet different requirements. Experiments with a large number of testing data show satisfactory results for the approach. Finally, a generic method for compressing and indexing multi—copy form documents is developed using template extraction and matching (TEM) strategies and OCR. De—skewing, location and distortion adjusting of form images are employed to realise the TEM method for practical applications. A statistical template extraction algorithm is developed using greyscale images created by overlapping a number of binary form images. The TEM method exploits the cmnponent—Ievel redundancy found in multi—copy form documents and reaches a high compression rate while keeping the original resolution and readability.
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13

Wong, Chi-hung, and 黃志雄. "Hand-written Chinese character recognition by hidden Markov models andradical partition." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31220058.

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14

劉健強 and Kin-keung Lau. "Preprocessing and postprocessing techniques for improving the performance of a Chinese character recognition system." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31210375.

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15

Wong, Pak-kwong. "Multifont printed Chinese character recognition system /." [Hong Kong : University of Hong Kong], 1991. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13068556.

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16

Ting, Voon-Cheung Roger. "Separation and recognition of connected handprinted capital English characters." Thesis, University of British Columbia, 1986. http://hdl.handle.net/2429/26747.

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The subject of machine recognition of connected characters is investigated. A generic single character recognizer (SCR) assumes there is only one character in the image. The goal of this project is to design a connected character segmentation algorithm (CCSA) without the above assumption. The newly designed CCSA will make use of a readily available SCR. The input image (e.g. a word with touching letters) is first transformed (thinned) into its skeletal form. The CCSA will then extract the image features (nodes and branches) and store them in a hierarchical form. The hierarchy stems from the left-to-right rule of writing of the English language. The CCSA will first attempt to recognize the first letter. When this is done, the first letter is deleted and the algorithm repeats. After extracting the image features, the CCSA starts to create a set of test images from the beginning of the word (i.e. beginning of the description). Each test image contains one more feature than its predecessor. The number of test images in the set is constrained by a predetermined fixed width or a fixed total number of features. The SCR is then called to examine each test image. The recognizable test image(s) in the set are extracted. Let each recognizable test image be denoted by C₁. For each C₁, a string of letters C₂, C₃, CL is formed. C₂ is the best recognized test image in a set of test images created after the deletion of C₁ from the beginning of the current word. C₃ through CL are created by the same method. All such strings are examined to determine which string contains the best recognized C₁. Experimental results on test images with two characters yield a recognition rate of 72.66%. Examples with more than two characters are also shown. Furthermore, the experimental results suggested that topologically simple test images can be more difficult to recognize than those which are topologically more complex.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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17

Hosseini, Habib Mir Mohamad. "Analysis and recognition of Persian and Arabic handwritten characters /." Title page, contents and abstract only, 1997. http://web4.library.adelaide.edu.au/theses/09PH/09phh8288.pdf.

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18

蔡健群 and Kin-kwan Choi. "Recognition of printed Chinese characters using a neural network." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31210247.

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19

Choi, Kin-kwan. "Recognition of printed Chinese characters using a neural network /." [Hong Kong : University of Hong Kong], 1991. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13166578.

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20

黃伯光 and Pak-kwong Wong. "Multifont printed Chinese character recognition system." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31210600.

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21

Ng, Pak-hung David. "The predominant role of visual codes in Chinese character recognition." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36910314.

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22

Ng, Pak-hung David, and 伍柏鴻. "The predominant role of visual codes in Chinese character recognition." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36910314.

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23

Zheng, Zhonghua. "Chinese characters and word recognition: An analysis and a model." Thesis, University of Ottawa (Canada), 1990. http://hdl.handle.net/10393/5573.

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Designations have been used very inconsistently in deciphering the nature of the Chinese writing system, ranging from pictographic, ideographic, logographic, to morphemic, phonosemantic, ideophonographic, and even to logosyllabic, word syllabic, morphosyllabic, etc. Implicit in the inconsistence is a set of hypotheses that Chinese is not a phonetic script, Chinese characters are represented in the right hemisphere and thus are processed in a picture-like fashion, and that recognizing Chinese characters does not involve phonological mediation, and so on. This thesis provides a thorough discussion of the linguistic structure underlying the organization of Chinese characters, and offers a perspective on the linguistic organization and the psycholinguistic processes involved in the recognition of Chinese characters. Misconceptions and fallacies concerning Chinese characters in both linguistic and cognitive areas are challenged and clarified. The thesis begins with a linguistic analysis of Chinese characters, focussing on the formal properties around which processing interpretations revolve. It then discusses issues of visual, hemispheric and cognitive processing of Chinese characters (e.g., how a Chinese character is visually detected? are Chinese characters represented in the right hemisphere? how are they processed in the two hemispheres? under what circumstances are Chinese characters visually accessed? and through what means if a Chinese character is to be phonologically coded? etc.). Lastly, an interactive model of Chinese character recognition is proposed. It is hoped that the groundwork may serve as the basis for proper experimental psycholinguistic research in future.
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24

Lee, Sai-ho, and 李世豪. "Recognition of components of Chinese characters by Hong Kong student =." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B3764791X.

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25

Ding, Wen. "A developmental study of phonological activation in Chinese character recognition." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/HKUTO/record/B39559087.

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26

Lee, Sai-ho. "Recognition of components of Chinese characters by Hong Kong student Xianggang xue sheng ren du bu tong bu jian zu he han zi de shi bie yan jiu /." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B3764791X.

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27

Bult, Timothy Paul. "Schema labelling applied to hand-printed Chinese character recognition." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26175.

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Hand-printed Chinese character recognition presents an interesting problem for Artificial Intelligence research. Input data in the form of arrays of pixel values cannot be directly mapped to unique character identifications because of the complexity of the characters. Thus, intermediate data structures are necessary, which in turn lead to a need to represent knowledge of the characters' composition. Building the intermediate constructs for these hand-printed characters necessarily involves choices among ambiguities, the set of which is so large that an efficient search algorithm becomes central to the recognition process. Schema labelling is a theory of how knowledge should be organized for recognition tasks in which composition structure is inherent in the domain, the composition entails ambiguity, and the ambiguity generates large search spaces. This thesis describes an implementation of an enhanced version of schema labelling for Chinese characters. The specific problems addressed by the enhancements, with some success, are (i) the segmentation of real images into objects usable by the schema system, (ii) the definition of schemas which adequately describe the generic composition of hand-printed Chinese characters, as well as common variations or vagaries, and (iii) the inclusion of sufficient "control knowledge" to prevent combinatorial explosion of the backtracking recognition process. Test characters for recognition systems can be classified along several dimensions. On the spectrum from type-set, through hand-printed, to hand-written forms, our system was tested on restricted hand-print, at a level somewhat more difficult than is normally attempted. On the spectrum of input types, from grey-scale pixel input through on-line stroke representations, our system was fully tested only at the high end, with complete synthetic strokes. We obtained a success rate of 57%, 12 out of the 21 characters tested. The principal success of the work is that characters of the complexity tested could be recognized at all, and in the impact schema labelling techniques had on that recognition.
Science, Faculty of
Computer Science, Department of
Graduate
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28

林梓鳳 and Tsz-fung Lam. "Chinese speakers' metalinguistic and processing representations of words and characters." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31226188.

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29

Lam, Tsz-fung. "Chinese speakers' metalinguistic and processing representations of words and characters /." Hong Kong : University of Hong Kong, 2001. http://sunzi.lib.hku.hk/hkuto/record.jsp?B23501698.

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30

Ding, Wen, and 丁雯. "A developmental study of phonological activation in Chinese character recognition." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39559087.

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31

Wong, Ing Hoo. "Design of a realtime high speed recognizer for unconstrained handprinted alphanumeric characters." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/25135.

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This thesis presents the design of a recognizer for unconstrained handprinted alphanumeric characters. The design is based on a thinning process that is capable of producing thinned images with well defined features that are considered essential for character image description and recognition. By choosing the topological points of the thinned ('line') character image as these desired features, the thinning process achieves not only a high degree of data reduction but also transforms a binary image into a discrete form of line drawing that can be represented by graphs. As a result powerful graphical analysis techniques can be applied to analyze and classify the image. The image classification is performed in two stages. Firstly, a technique for identifying the topological points in the thinned image is developed. These topological points represent the global features of the image and because of their invariance to elastic deformations, they are used for image preclassification. Preclassification results in a substantial reduction in the entropy of the input image. The subsequent process can concentrate only on the differentiation of images that are topologically equivalent. In the preclassifier simple logic operations localized to the immediate neighbourhood of each pixel are used. These operations are also highly independent and easy to implement using VLSI. A graphical technique for image extraction and representation called the chain coded digraph representation is introduced. The technique uses global features such as nodes and the Freeman's chain codes for digital curves as branches. The chain coded digraph contains all the information that is present in the thinned image. This avoids using the image feature extraction approach for image description and data reduction (a difficult process to optimize) without sacrificing speed or complexity. After preclassification, a second stage of the recognition process analyses the chain coded digraph using the concept of attributed relational graph (ARG). ARG representation of the image can be obtained readily through simple transformations or rewriting rules from the chain coded digraph. The ARG representation of an image describes the shape primitives in the image and their relationships. Final classification of the input image can be made by comparing its ARG with the ARGs of known characters. The final classification involves only the comparison of ARGs of a predetermined topology. This information is crucial to the design of a matching algorithm called the reference guided inexact matching procedure, designed for high speed matching of character image ARGs. This graph matching procedure is shown to be much faster than other conventional graph matching procedures. The designed recognizer is implemented in Pascal on the PDP11/23 and VAX 11/750 computer. Test using Munson's data shows a high recognition rate of 91.46%. However, the recognizer is designed with the aim of an eventual implementation using VLSI and also as a basic recognizer for further research in reading machines. Therefore its full potential is yet to be realized. Nevertheless, the experiments with Munson's data illustrates the effectiveness of the design approach and the advantages it offers as a basic system for future research.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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32

Lo, On-ting, and 羅安庭. "Chinese character recognition : studies of complexity effect on recognition efficiency, spatial frequency characteristics, crowding and expertise." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/197116.

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Chinese characters are used by about one-fifth of the world population. Each character can generally be analyzed and represented at three orthographic levels including single stroke, component and whole character. Regardless of the number of strokes a Chinese character has, it always occupies a square area. Such special spatial layout leads to a great variation in stroke density, i.e., visual complexity, among Chinese characters. Here in this thesis, the effects of visual complexity on Chinese character recognition were examined to investigate the visual processing of Chinese characters in both central and peripheral vision. Empirical findings from four psychophysical studies will be reported. First, the efficiency of detecting and recognizing Chinese characters of different complexity levels was studied. Human recognition of a more complex Chinese character was found to be generally less efficient than that of a simpler one. The relationship between efficiency and complexity had a log-log slope of approximately -1, suggesting that the basic features for recognizing a single Chinese character might be less complex than the simplest object used, which is a single stroke. Analysis results of the detection and recognition efficiency were consistent with a two-stage processing model of Chinese character recognition—feature detection followed by feature integration. Results in peripheral vision suggested that the feature integration process was adversely influenced by internal crowding. Second, the spatial frequency characteristics of recognizing Chinese characters of different complexity levels were examined. The results showed that the peak tuning frequency for recognizing a more complex Chinese character was higher and the bandwidth of the spatial tuning functions was narrower than for recognizing a simpler character. In addition, the effects of size on such spatial frequency characteristics depended on the complexity level. The comparison of human performance against the corresponding performance of a CSF-limited ideal observer model implied that the processing mechanism of recognizing simple and complex characters was different. Moreover, similar results were observed among native Chinese and non-Chinese readers, suggesting that expertise might not influence front end processing properties such as the spatial frequency characteristics of Chinese character recognition. Third, the importance of utilizing spatial frequency information of different orientations (i.e., horizontal versus vertical) in Chinese character recognition was investigated. Results showed higher efficiency in utilizing vertical than horizontal stroke information for Chinese character recognition among native Chinese readers whereas non-Chinese readers used both vertical and horizontal stroke information similarly. Fourth, the effects of the target-flanker similarity in complexity on crowding in Chinese character recognition were examined. The results suggested that the behavior of feature integration process in peripheral vision might be consistent with summation theory, which stresses on the relationship between the processing capacity of neurons and the processing demand of stimuli. The “excessive feature integration explanation” of crowding was also discussed in the context of the current findings. Building on previous research in the literature, results from the four studies in this thesis were synthesized in a proposal of a visual information processing model for Chinese character recognition.
published_or_final_version
Psychology
Doctoral
Doctor of Philosophy
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33

Wong, Pak-kwong. "Statistical language models for Chinese recognition : speech and character /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B20158725.

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34

Sae-Tang, Sutat. "A systematic study of offline recognition of Thai printed and handwritten characters." Thesis, University of Southampton, 2011. https://eprints.soton.ac.uk/206079/.

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Thai characters pose some unique problems, which differ from English and other oriental scripts. The structure of Thai characters consists of small loops combined with curves and there is an absence of spaces between each word and sentence. In each line, moreover, Thai characters can be composed on four levels, depending on the type of character being written. This research focuses on OCR for the Thai language: printed and offline handwritten character recognition. An attempt to overcome the problems by simple but effective methods is the main consideration. A printed OCR developed by the National Electronics and Computer Technology Center (NECTEC) uses Kohonen self- organising maps (SOMs) for rough classification and back-propagation neural networks for fine classification. An evaluation of the NECTEC OCR is performed on a printed dataset that contains over 0.6 million tokens. Comparisons of the classifier, with and without the aspect ratio, and with and without SOMs, yield small, but statistically significant differences in recognition rate. A very straightforward classifier, the nearest neighbour, was examined to evaluate overall recognition performance and to compare with the classifier. It shows a significant improvement in recognition rate (about 98%) over the NECTEC classifier (about 96%) on both the original and distorted data (rotated and noisy), but at the expense of longer recognition times. For offline handwritten character recognition, three different classifiers are evaluated on three different datasets that contain, on average, approximately 10,000 tokens each. The neural network and HMMs are more effective and give higher recognition rates than the nearest neighbour classifier on three datasets. The best result obtained from the HMMs is 91.1% on ThaiCAM dataset. However, when evaluated on a different dataset, the recognition rates drastically reduce, due to differences in many aspects of online and offline handwritten data. An improvement in classification rates was obtained by adjusting the stroke width of a character in the online handwritten dataset (12 percentage points) and combining the training sets from the three datasets (7.6 percentage points). A boosting algorithm called AdaBoost yields a slight improvement in recognition rate (1.2 percentage points) over the original classifiers (without applying the AdaBoost algorithm).
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35

Chen, Songqing. "Development of a neural network based software package for the automatic recognition of license plate characters." Ohio : Ohio University, 1992. http://www.ohiolink.edu/etd/view.cgi?ohiou1172092299.

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36

Wang, Ling. "The impact of multimedia on Chinese learners' recognition of characters a quantitative and qualitative study /." online access from Digital Dissertation Consortium, 2005. http://libweb.cityu.edu.hk/cgi-bin/er/db/ddcdiss.pl?3210808.

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37

Wong, Wai-man Vivian. "The role of phonological consistency and family size of phonetic radicals in reading Chinese characters in school-aged children in Hong Kong." Click to view the E-thesis via HKU Scholars Hub, 2003. http://lookup.lib.hku.hk/lookup/bib/B38890926.

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Thesis (B.Sc.)--University of Hong Kong, 2003.
"A dissertation submitted in partial fulfilment of the requirements for the Bachelor of Science (Speech and Hearing Sciences), The University of Hong Kong, April 30, 2003." Includes bibliographical references (p. 29-30) Also available in print.
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38

陳國評 and Kwok-ping Chan. "Fuzzy set theoretic approach to handwritten Chinese character recognition." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B30425876.

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39

黃伯光 and Pak-kwong Wong. "Statistical language models for Chinese recognition: speech and character." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31239456.

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40

Kwok, Ching-man Emily. "The discrepancy in the studies on the change of regularity effect in Chinese characters reading across grades methodological differences? /." Click to view the E-thesis via HKU Scholars Hub, 2003. http://lookup.lib.hku.hk/lookup/bib/B38888737.

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Thesis (B.Sc.)--University of Hong Kong, 2003.
"A dissertation submitted in partial fulfilment of the requirements for the Bachelor of Science (Speech and Hearing Sciences), The University of Hong Kong, April 30, 2003." Includes bibliographical references (p. 29-31) Also available in print.
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41

Lin, Yeu-Chang, and 林裕章. "Using Confusion Characters to Improve Character Recognition Rate." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/34907033760970274876.

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碩士
國立交通大學
資訊工程學系
84
This thesis proposes a confusion set analysis approach to improve character recognition rate. We collect all confused characters of a character by analyzing the recognition results of 100 training samples taken from the CCL/HCCR database. In the training phase, a character is first recognized by an OCR system OCR1 and top five candidates are outputted. Each candidate of the recognition results is assigned a weight in reversed-rank. After all training samples of all 5401 characters are trained, we create a confusion set for each character. If the reversed-rank sum of an output candidate is greater than a threshold, the input character is stored in the confusion set of the output candidate. Similar characters in a confusion set are different in certain parts. We select features in these distinct parts to distinguish the similar characters. However, it is hard to select suitable features when the size of a confusion set is large. We cluster the characters of the confusion set into subgroups by using crossing count features. Then, we calculate the weights for all features among the characters in each subgroup to select the most distinguishable features. In the recognition phase, we obtain the most possible output character by the OCR system OCR1 for each input character. The characters in the confusion set with respect to the output character are recognized by another OCR system OCR2 to find the final recognition result. Experimental results show that the hit rates of the subgroups of the confusion sets are 93. 76% and the average size of the subgroups is 9.01. The final recognition rate for our system is 86.97%.
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42

Huang, Jacky, and 黃鉦晏. "Fuzzy decision and characters recognition." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/35920022067004777388.

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43

Gong, Shyh-Jier, and 龔世傑. "Recognition of handwritten digit characters." Thesis, 1993. http://ndltd.ncl.edu.tw/handle/19034124518507636417.

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碩士
大同工學院
資訊工程研究所
81
This paper presents a methodology for classifying syntactic patterns is using a feature matching against a set of proto- otypes. The prototypes are first classified and arranged into a hierarchical structure that facilitates this matching. Image of characters are described by a sequence of features extracted from the chain codes of their contours. A rotatio- nally invariant string distance measure is defined that com- pared two feature strings. The methodology discussed in this paper is compared to a nearest neighbor classifier that use 2,010 prototypes. The proposed technique can get a recognit- ion rate of greater than 97 percent, and the recognition sp- eed is 0.5 sec/char.
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44

Liang, Hao-Po, and 梁浩伯. "The Action Research of Direct Teaching Chinese Characters to Preschool Children’s Character Recognition." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/74178509709454582854.

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碩士
國立臺中教育大學
教育學系
102
This research used action research, discuss the implementation of direct teaching Chinese Characters of San Zi Jing. In the process, trying to development variety of teaching strategies, and promote the quantity of Chinese character recognition. The subjects of the study were 24 children in kindergarten of Changhua County. Implementation of ten weeks, five times a week, every thirty minutes of direct teaching Chinese characters courses. In the course of study, the researcher conducted data collection and analysis through literacy scale, teachers’ interviews, observation records, teaching notes, parents surveys, parents qualitative feedbacks, course records, summarized the conclusions of this study are as follows: 1. Let preschool to read aloud texts, recite texts, master the voice of the texts is the first stage of direct teaching Chinese characters; Secondly , establishing a link of Chinese characters pronunciation and shape with variety of teaching strategies is the next stage of direct teaching Chinese characters. 2. Direct teaching Chinese characters can effectively promote the quantity of Chinese character recognition and parents’ affirmative generally. 3. Difficulties encountered in the process have: the degree of dedication in reading texts, the interference of teaching, the appropriate of seating arrangements, checklist effectiveness of these course, the particularity of the subjects. Based on the above conclusions, researcher suggestions on teaching practice, including suggestions for teachers, parents and suggestions to recommend to kindergarten, as well as recommendations on the follow-up study. Providing education conducted Chinese character teaching partners and researchers by direct teaching Chinese characters refer to and apply.
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45

Tai, Yu-Ho, and 戴宇核. "The Effect of Character-Based Teaching Materials on Chinese Characters’ Recognition and Writing." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/7zpw27.

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Abstract:
碩士
國立臺灣師範大學
華語文教學系
106
Recently, the method of teaching Chinese Characters has drawn great attention in the field of Chinese Teaching. Studies on different teaching methods and strategies have become hot research issues. How to improve the reading(recognition) and writing ability of students at primary level is considered greatly by teachers and researchers. Referring to the theory of serial position effect, this study introduced Chinese Characters input and output path models. At the same time, the teaching strategies were divided into two groups, that is, Pronunciation as priority group and Writing as priority group. There is no previous exploration on whether teaching pronunciation first or writing first can mostly benefit Chinese Characters’ reading(recognition) ability and(or) writing ability. Therefore, the researcher used the teaching strategies based on the two models as mentioned before as well as the traditional teaching method of sentence-based teaching to design the research and conduct the empirical research. The participants of this research were 177 beginning level learners of Chinese language, including Filipino-Chinese and non-Filipino-Chinese, in 8th grade at Grace Christian College, Philippines. After analyzing the data, three conclusions were obtained as follows: 1.The learners who accepted the character-based approach improved their ability of reading(recognition) and writing Chinese Characters more than those accepted sentence-based approach learners. 2.The results of this research consisted with the primary effect theory of serial position effect. The ability of Chinese Characters’ reading(recognition) of students in the Pronunciation as priority group was significantly higher than that of students in other groups. While the ability of Chinese Characters’ writing of students in Writing as priority group was significantly higher than that of students in other groups. 3.In general, the Filipino-Chinese students’ ability of reading(recognition) and writing was significantly higher than that of non-Filipino-Chinese students. This study may provide a reference for teachers and researchers in Chinese teaching practice.
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46

Jian, Jia-Ching, and 簡嘉慶. "Very High Precision Optical Character Recognition For Clean-Fixed-Sized True Type Characters." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/29nd45.

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碩士
國立中央大學
資訊工程學系
105
Optical Character Recognition has been studied for many years. However, no OCR tools can claim 100% recognition rate because of the variation in image quality, documentation layout, character fonts and sizes. When there are changes in one of them, recognition rate is often greatly impacted. Korat is an image-based test regression tool developed in our lab. Korat captures the screen image from a system under test. Therefore, the image is clean, no noises, and no rotation. Based on this condition, we do not deal with situations like image noises, which makes OCR a difficult problem in this thesis. In Korat's practical applications, nearly 100% recognition rate is often required. So even there are many existing OCR tools with 88-95% recognition rate, they do not meet the requirements of Korat's practical applications. In this research, we combine the template matching and dynamic programming algorithm to find the optimal solution with the smallest sum of remaining pixels in all possible combinations of recognition so that the recognition rate could be achieved 100% at nearly.
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47

"Video-based handwritten Chinese character recognition." 2003. http://library.cuhk.edu.hk/record=b6073522.

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Abstract:
by Lin Feng.
"June 2003."
Thesis (Ph.D.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (p. [114]-130).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Mode of access: World Wide Web.
Abstracts in English and Chinese.
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48

Silva, Rui. "Mobile framework for recognition of musical characters." Dissertação, 2013. http://hdl.handle.net/10216/73771.

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49

Chen, Yang-En, and 陳仰恩. "Matching Topological Structures for Handwritten Characters Recognition." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/szkjv3.

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Abstract:
碩士
國立臺灣大學
資訊工程學研究所
105
This work presents a matching process to resolve the variable distortions for recognition of handwritten characters. It can tolerate difficult distortions by preserving the topological structure of the character. The unknown character and all templates are represented in advance by features that resemble the receptive fields of visual system. The templates are loaded with flexible and variable features along their skeletons. These flexible features can tolerate local distortions. The global operations, shift, rotation, and scale, are applied to revise the whole template according to certain highly matched features. After these operations, the matched feature in the revised template will overlap its corresponding feature in the unknown character as much as possible. New matching score can be calculated for each feature of the revised template. This kind revision can be operated iteratively. The recognition is accomplished for the template which received the highest whole score. This work illustrates this matching process and its operations. This process indirectly overcomes difficult distortion problems.
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50

TSAI, CHEN-CHEN, and 蔡真真. "Chinese Characters Recognition within Wroking Memory Paradigm." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/92105551040488257492.

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Abstract:
碩士
國立中正大學
心理學研究所
87
Abstract Chinese characters are mostly constructed of a part with phonological information and a part with meaning(radical). Because of this difference with alphabetic system, word recognition has been always a popular topic in psychology, especially the role of phonological representations and orthographic representations in Chinese characters recognition. Many studies have found the importance and necessity of phonological representations in lexical access of Chinese characters. Some studies have found that orthographic representations play some role in lexical access of Chinese characters. There seems to be two routs of processing Chinese characters. These two routs appear to match the process of verbal and visual working memory proposed by Baddeley(1986).In this study, we want to explore this relationship. There are three experiments in this study. We designed phonological and visual concurrent tasks intervene the processing of Chinese characters and saw if these tasks influence the performance of Chinese character recognition. In experiment 1, We presented six characters successively with each 230 ms. After that subjects performed an intervention judgment task , then character recognition. We found there was a significant advantage of phonological representations in high frequency characters, but no difference between phonological and orthographic representations in low frequency. In experiment 2, after we shortened the presentation time, number of Chinese characters, switched characters recognition and intervention task and changed the stimulus material to extremely unfamiliar characters in low frequency characters, the difference between phonological and orthographic representations is not significant. In experiment 3, maintaining the condition as in experiment 2, we prolonged the presentation time and found that when phonological loading was heavy, subjects preferred visual cue and when visual loading was heavy, they preferred phonological cue. It shows in this study that, phonological information plays an important role in Chinese character recognition, just as in alphabetic system. Only when phonological loading is too heavy, orthographic information will be used.
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