The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kaedah baru untuk pengecaman corak automatik dibentangkan. Kaedah ini adalah berdasarkan algoritma Pemadanan Segmen dan Jiran yang boleh digunakan untuk mengenal pasti abjad terkenal, glyph kompleks dan skrip Arab yang terkenal. Dalam kerja ini beberapa kaedah yang dilaporkan berbeza telah dinilai pada aksara Latin, Cina dan glif Maya dengan objektif utama untuk memilih kaedah yang mempunyai kelajuan pemprosesan dan gred pengiktirafan tertinggi. Kes glif Maya adalah lebih rumit disebabkan oleh sejumlah besar elemen dalam mana-mana glif, variasi ketara bagi perwakilan atau tulisannya, terdapat lebih daripada 800 kelas glif dan kebanyakannya dengan komponen dan lokasi yang serupa. Kaedah Cadangan Padanan Segmen dan Jiran telah dibangunkan berdasarkan set kabur dan konsep fungsi keahlian yang boleh ditakrifkan semasa manipulasi dengan rangka glif. Seterusnya, tahap padanan dengan corak yang dipratentukan digunakan untuk pengecaman segmen dan tafsiran keseluruhan glif. Ciri utama proses pengecaman ialah tahap pemadanan, masa pemprosesan, gred keahlian, dan kecekapan tafsiran yang penting untuk imej glif yang tidak lengkap. Berdasarkan kaedah yang dicadangkan, perisian khas RECGLYM (Pengiktirafan Glyphs Maya) telah direka bentuk untuk platform komputer SUN dan Intel PC. Kelebihan kaedah Padanan Segmen dan Jiran yang dicadangkan ialah pemprosesan imej yang cepat dan kebarangkalian tinggi tafsiran glif kompleks. Kaedah yang dicadangkan boleh digunakan dalam aplikasi yang berbeza, contohnya, untuk pemilihan dan mendiagnosis anomali tertentu dengan cara pemprosesan imej X-ray atau untuk navigasi Internet dan mencari maklumat dengan analisis persamaan imej dengan corak yang telah ditetapkan.
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Salinan
Oleg STAROSTENKO, Jose Antonio NEME, "Automatic Complex Glyphs Recognition and Interpretation" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 10, pp. 2154-2160, October 1999, doi: .
Abstract: The novel method for automatic pattern recognition is presented. This method is based on Segment and Neighbors Matching algorithm which can be applied for recognizing of distinct well-known alphabets, complex glyphs, and Arabic scripts. In this work some different reported methods have been evaluated on Latin, Chinese characters, and Mayan glyphs with the principle objective to select those with the highest processing speed and recognition grade. The case of Mayan glyphs is more complicated due to a big number of elements in any glyph, significant variations of their representation or writing, there are more than 800 classes of glyphs and many of them with similar components and locations. The proposed method of Segments and Neighbors Matching has been developed on base of fuzzy sets and membership functions concept which can be defined during manipulation with the glyph skeleton. Next, levels of matching with predefined patterns are used for segments recognition and interpretation of whole glyph. The main characteristics of recognizing process are matching level, time of processing, grade of membership, and efficiency of interpretation that is important for incomplete glyphs images. On base of proposed method the special software RECGLYM (Mayan Glyphs Recognition) has been designed for the SUN and Intel PC computers platforms. The advantages of the proposed Segments and Neighbors Matching method are quick image processing and high probability of complex glyphs interpretation. The proposed method could be used in different applications, for example, for selection and diagnose of certain anomalies by means of processing of X-ray images or for Internet navigation and searching information searching by image similarity analysis with predefined pattern.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_10_2154/_p
Salinan
@ARTICLE{e82-a_10_2154,
author={Oleg STAROSTENKO, Jose Antonio NEME, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Automatic Complex Glyphs Recognition and Interpretation},
year={1999},
volume={E82-A},
number={10},
pages={2154-2160},
abstract={The novel method for automatic pattern recognition is presented. This method is based on Segment and Neighbors Matching algorithm which can be applied for recognizing of distinct well-known alphabets, complex glyphs, and Arabic scripts. In this work some different reported methods have been evaluated on Latin, Chinese characters, and Mayan glyphs with the principle objective to select those with the highest processing speed and recognition grade. The case of Mayan glyphs is more complicated due to a big number of elements in any glyph, significant variations of their representation or writing, there are more than 800 classes of glyphs and many of them with similar components and locations. The proposed method of Segments and Neighbors Matching has been developed on base of fuzzy sets and membership functions concept which can be defined during manipulation with the glyph skeleton. Next, levels of matching with predefined patterns are used for segments recognition and interpretation of whole glyph. The main characteristics of recognizing process are matching level, time of processing, grade of membership, and efficiency of interpretation that is important for incomplete glyphs images. On base of proposed method the special software RECGLYM (Mayan Glyphs Recognition) has been designed for the SUN and Intel PC computers platforms. The advantages of the proposed Segments and Neighbors Matching method are quick image processing and high probability of complex glyphs interpretation. The proposed method could be used in different applications, for example, for selection and diagnose of certain anomalies by means of processing of X-ray images or for Internet navigation and searching information searching by image similarity analysis with predefined pattern.},
keywords={},
doi={},
ISSN={},
month={October},}
Salinan
TY - JOUR
TI - Automatic Complex Glyphs Recognition and Interpretation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2154
EP - 2160
AU - Oleg STAROSTENKO
AU - Jose Antonio NEME
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 1999
AB - The novel method for automatic pattern recognition is presented. This method is based on Segment and Neighbors Matching algorithm which can be applied for recognizing of distinct well-known alphabets, complex glyphs, and Arabic scripts. In this work some different reported methods have been evaluated on Latin, Chinese characters, and Mayan glyphs with the principle objective to select those with the highest processing speed and recognition grade. The case of Mayan glyphs is more complicated due to a big number of elements in any glyph, significant variations of their representation or writing, there are more than 800 classes of glyphs and many of them with similar components and locations. The proposed method of Segments and Neighbors Matching has been developed on base of fuzzy sets and membership functions concept which can be defined during manipulation with the glyph skeleton. Next, levels of matching with predefined patterns are used for segments recognition and interpretation of whole glyph. The main characteristics of recognizing process are matching level, time of processing, grade of membership, and efficiency of interpretation that is important for incomplete glyphs images. On base of proposed method the special software RECGLYM (Mayan Glyphs Recognition) has been designed for the SUN and Intel PC computers platforms. The advantages of the proposed Segments and Neighbors Matching method are quick image processing and high probability of complex glyphs interpretation. The proposed method could be used in different applications, for example, for selection and diagnose of certain anomalies by means of processing of X-ray images or for Internet navigation and searching information searching by image similarity analysis with predefined pattern.
ER -