• Title, Summary, Keyword: grapheme extraction

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A Study on Grapheme and Grapheme Recognition Using Connected Components Grapheme for Machine-Printed Korean Character Recognition

  • Lee, Kyong-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.9
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    • pp.27-36
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    • 2016
  • Recognition of grapheme is a very important process in the recognition within 'Hangul(Korean written language)' letters using phoneme recognition. It is because the success or failure in the recognition of phoneme greatly affects the recognition of letters. For this reason, it is reported that separation of phonemes is the biggest difficulty in the phoneme recognition study. The current study separates and suggests the new phonemes that used the connective elements that are helpful for dividing phonemes, recommends the features for recognition of such suggested phonemes, databases this, and carried out a set of experiments of recognizing phonemes using the suggested features. The current study used 350 letters in the experiment of phoneme separation and recognition. In this particular kind of letters, there were 1,125 phonemes suggested. In the phoneme separation experiment, the phonemes were divided in the rate of 100%, and the phoneme recognition experiment showed the recognition rate of 98% in recognizing only 14 phonemes into different ones.

Graphemes Segmentation for Arabic Online Handwriting Modeling

  • Boubaker, Houcine;Tagougui, Najiba;El Abed, Haikal;Kherallah, Monji;Alimi, Adel M.
    • Journal of Information Processing Systems
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    • v.10 no.4
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    • pp.503-522
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    • 2014
  • In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

A study on Machine-Printed Korean Character Recognition by the Character Composition form Information of the Graphemes and Graphemes using the Connection Ingredient and by the Vertical Detection Information in the Weight Center of Graphemes

  • Lee, Kyong-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.3
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    • pp.97-105
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    • 2017
  • This study is the realization study recognizing the Korean gothic printing letter. This study defined the new grapheme by using the connection ingredient and had the graphemes recognized by means of the feature dots of the isolated dot, end dot, 2-line gathering dots, more than 3 lines gathering dots, and classified the characters by means of the arrangement information of the graphemes and the layers that the graphemes form within the characters, and made the character database for the recognition by using them. The layers and the arrangement information of the graphemes consisting in the characters were presumed by using the weight center position information of the graphemes extracted from the characters to recognize and the information of the graphemes obtained by vertically exploring from the weight center of each grapheme, and it recognized the characters by judging and comparing the character groups of the database by means of the information which was secured this way. 350 characters were used for the character recognition test and about 97% recognition result was obtained by recognizing 338 characters.

The Recognition of Grapheme 'ㅁ', 'ㅇ' Using Neighbor Angle Histogram and Modified Hausdorff Distance (이웃 각도 히스토그램 및 변형된 하우스도르프 거리를 이용한 'ㅁ', 'ㅇ' 자소 인식)

  • Chang Won-Du;Kim Ha-Young;Cha Eui-Young;Kim Do-Hyeon
    • Journal of Korea Multimedia Society
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    • v.8 no.2
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    • pp.181-191
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    • 2005
  • The classification error of 'ㅁ', 'ㅇ' is one of the main causes of incorrect recognition in Korean characters, but there haven't been enough researches to solve this problem. In this paper, a new feature extraction method from Korean grapheme is proposed to recognize 'ㅁ', 'ㅇ'effectively. First, we defined an optimal neighbor-distance selection measure using modified Hausdorff distance, which we determined the optimal neighbor-distance by. And we extracted neighbor-angle feature which was used as the effective feature to classify the two graphemes 'ㅁ', 'ㅇ'. Experimental results show that the proposed feature extraction method worked efficiently with the small number of features and could recognize the untrained patterns better than the conventional methods. It proves that the proposed method has a generality and stability for pattern recognition.

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A Study on Automation about Painting the Letters to Road Surface

  • Lee, Kyong-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.1
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    • pp.75-84
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    • 2018
  • In this study, the researchers attempted to automate the process of painting the characters on the road surface, which is currently done by manual labor, by using the information and communication technology. Here are the descriptions of how we put in our efforts to achieve such a goal. First, we familiarized ourselves with the current regulations about painting letters or characters on the road, with reference to Road Mark Installation Management Manual of the National Police Agency. Regarding the graphemes, we adopted a new one using connection components, in Gothic print characters which was within the range of acceptance according to the aforementioned manual. We also made it possible for the automated program to recognize the graphemes by means of the feature dots of the isolated dots, end dots, 2-line gathering dots, and gathering dots of 3 lines or more. Regarding the database, we built graphemes database for plotting information, classified the characters by means of the arrangement information of the graphemes and the layers that the graphemes form within the characters, and last but not least, made the character shape information database for character plotting by using such data. We measured the layers and the arrangement information of the graphemes consisting the characters by using the information of: 1) the information of the position of the center of gravity, and 2) the information of the graphemes that was acquired through vertical exploration from the center of gravity in each grapheme. We identified and compared the group to which each character of the database belonged, and recognized the characters through the use of the information gathered using this method. We analyzed the input characters using the aforementioned analysis method and database, and then converted into plotting information. It was shown that the plotting was performed after the correction.

Character Region Detection Using Structural Features of Hangul Vowel (한글 모음의 구조적 특징을 이용한 문자영역 검출 기법)

  • Park, Jong-Cheon;Lee, Keun-Wang;Park, Hyoung-Keun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.2
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    • pp.872-877
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    • 2012
  • We proposes the method to detect the Hangul character region from natural image using topological structural feature of Hangul grapheme. First, we transform a natural image to a gray-scale image. Second, feature extraction performed with edge and connected component based method, Edge-based method use a Canny-edge detector and connected component based method applied the local range filtering. Next, if features are not corresponding to the heuristic rule of Hangul character, extracted features filtered out and select candidates of character region. Next, candidates of Hangul character region are merged into one Hangul character using Hangul character merging algorithm. Finally, we detect the final character region by Hangul character class decision algorithm. Experimental result, proposed method could detect a character region effectively in images that contains a complex background and various environments. As a result of the performance evaluation, A proposed method showed advanced results about detection of Hangul character region from mobile image.