Triangle Shape Feature based on Selected Centroid for Arabic Subword Handwriting
Features are normally modelled based on color, texture and shape. However, some features may have different constraints based on types, styles and pattern of an image. The Arabic subword handwriting, for example, cannot be recognized by color and not suitable to be characterized based on texture. Th...
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description | Features are normally modelled based on color, texture and shape. However, some features may have different constraints based on types, styles and pattern of an image. The Arabic subword handwriting, for example, cannot be recognized by color and not suitable to be characterized based on texture. Therefore, features based on shape are suitable to be used for recognizing Arabic subword handwriting since each of the character has various characteristics such as diacritics, thinning and strokes. These characteristics can contribute to particular a shape that is unique and can represent Arabic subword handwriting. Currently, geometry shape such as triangle has been adopted to extract useful features based on triangle properties without implicating any triangle form. In order to increase classification accuracy, these properties have been categorized into several zones where the number of features produced is directly proportional to the number of zones. Nevertheless, shape representation does not implicate any triangle properties such as ratio of side, angle and gradient. By using shape representation, it helps in reducing the number of features. Thus, this paper presents feature based on triangle shape that can represent the identity of Arabic subword handwriting. The method based on triangle shape identifies three main coordinates of triangle formed based on selected centroids. The AHDB dataset is used as a testing data. The Support Vector Machine (SVM) and Random Forest (RF), respectively were used to measure the accuracy of the proposed method using triangle shape as a feature. The accuracy results have shown better outcome with 77.65% (SVM) and 76.43% (RF), which prove the feature based on triangle shape is applicable for Arabic subword handwriting recognition. |
doi_str_mv | 10.14569/IJACSA.2018.091224 |
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However, some features may have different constraints based on types, styles and pattern of an image. The Arabic subword handwriting, for example, cannot be recognized by color and not suitable to be characterized based on texture. Therefore, features based on shape are suitable to be used for recognizing Arabic subword handwriting since each of the character has various characteristics such as diacritics, thinning and strokes. These characteristics can contribute to particular a shape that is unique and can represent Arabic subword handwriting. Currently, geometry shape such as triangle has been adopted to extract useful features based on triangle properties without implicating any triangle form. In order to increase classification accuracy, these properties have been categorized into several zones where the number of features produced is directly proportional to the number of zones. Nevertheless, shape representation does not implicate any triangle properties such as ratio of side, angle and gradient. By using shape representation, it helps in reducing the number of features. Thus, this paper presents feature based on triangle shape that can represent the identity of Arabic subword handwriting. The method based on triangle shape identifies three main coordinates of triangle formed based on selected centroids. The AHDB dataset is used as a testing data. The Support Vector Machine (SVM) and Random Forest (RF), respectively were used to measure the accuracy of the proposed method using triangle shape as a feature. The accuracy results have shown better outcome with 77.65% (SVM) and 76.43% (RF), which prove the feature based on triangle shape is applicable for Arabic subword handwriting recognition.</description><identifier>ISSN: 2158-107X</identifier><identifier>EISSN: 2156-5570</identifier><identifier>DOI: 10.14569/IJACSA.2018.091224</identifier><language>eng</language><publisher>West Yorkshire: Science and Information (SAI) Organization Limited</publisher><subject>Accuracy ; Centroids ; Color ; Feature extraction ; Handwriting ; Handwriting recognition ; Object recognition ; Representations ; Support vector machines ; Texture recognition ; Triangles</subject><ispartof>International journal of advanced computer science & applications, 2018, Vol.9 (12)</ispartof><rights>2018. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). 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However, some features may have different constraints based on types, styles and pattern of an image. The Arabic subword handwriting, for example, cannot be recognized by color and not suitable to be characterized based on texture. Therefore, features based on shape are suitable to be used for recognizing Arabic subword handwriting since each of the character has various characteristics such as diacritics, thinning and strokes. These characteristics can contribute to particular a shape that is unique and can represent Arabic subword handwriting. Currently, geometry shape such as triangle has been adopted to extract useful features based on triangle properties without implicating any triangle form. In order to increase classification accuracy, these properties have been categorized into several zones where the number of features produced is directly proportional to the number of zones. Nevertheless, shape representation does not implicate any triangle properties such as ratio of side, angle and gradient. By using shape representation, it helps in reducing the number of features. Thus, this paper presents feature based on triangle shape that can represent the identity of Arabic subword handwriting. The method based on triangle shape identifies three main coordinates of triangle formed based on selected centroids. The AHDB dataset is used as a testing data. The Support Vector Machine (SVM) and Random Forest (RF), respectively were used to measure the accuracy of the proposed method using triangle shape as a feature. The accuracy results have shown better outcome with 77.65% (SVM) and 76.43% (RF), which prove the feature based on triangle shape is applicable for Arabic subword handwriting recognition.</description><subject>Accuracy</subject><subject>Centroids</subject><subject>Color</subject><subject>Feature extraction</subject><subject>Handwriting</subject><subject>Handwriting recognition</subject><subject>Object recognition</subject><subject>Representations</subject><subject>Support vector machines</subject><subject>Texture recognition</subject><subject>Triangles</subject><issn>2158-107X</issn><issn>2156-5570</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNotkF1LwzAUhoMoOOZ-gTcBrzvz3eSyFOcmA4VO8C4kTTo7ZjPTluG_N66em_NePJzz8gBwj9ESMy7U4-alKKtiSRCWS6QwIewKzAjmIuM8R9eXLDOM8o9bsOj7A0pDFRGSzsDbLram2x89rD7NycOVN8MYPbSm9w6GDlb-6Osh5dJ3Qwytg02IsIjGtjWsRnsO0cG16dw5tkPb7e_ATWOOvV_87zl4Xz3tynW2fX3elMU2qykhQ8YtYqRJ_bmzjNCcGiMIaxj1SDCV57W0qZ-SyhPrmJPWM0uZo1YkFAlD5-BhunuK4Xv0_aAPYYxdeqmJ4IIRJSVKFJ2oOoa-j77Rp9h-mfijMdIXe3qyp__s6cke_QXaN2Fn</recordid><startdate>2018</startdate><enddate>2018</enddate><creator>Arbain, Nur Atikah</creator><creator>Sanusi, Mohd</creator><creator>Kamilah, Azah</creator><creator>Ramzani, Amirul</creator><creator>Tahir, Azrina</creator><general>Science and Information (SAI) Organization Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7XB</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>2018</creationdate><title>Triangle Shape Feature based on Selected Centroid for Arabic Subword Handwriting</title><author>Arbain, Nur Atikah ; Sanusi, Mohd ; Kamilah, Azah ; Ramzani, Amirul ; Tahir, Azrina</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c322t-5b042f1455db42373aa624f43e064977c8b683989e2bd4d8be4b34d3b673a06a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Accuracy</topic><topic>Centroids</topic><topic>Color</topic><topic>Feature extraction</topic><topic>Handwriting</topic><topic>Handwriting recognition</topic><topic>Object recognition</topic><topic>Representations</topic><topic>Support vector machines</topic><topic>Texture recognition</topic><topic>Triangles</topic><toplevel>online_resources</toplevel><creatorcontrib>Arbain, Nur Atikah</creatorcontrib><creatorcontrib>Sanusi, Mohd</creatorcontrib><creatorcontrib>Kamilah, Azah</creatorcontrib><creatorcontrib>Ramzani, Amirul</creatorcontrib><creatorcontrib>Tahir, Azrina</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Proquest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>International journal of advanced computer science & applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Arbain, Nur Atikah</au><au>Sanusi, Mohd</au><au>Kamilah, Azah</au><au>Ramzani, Amirul</au><au>Tahir, Azrina</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Triangle Shape Feature based on Selected Centroid for Arabic Subword Handwriting</atitle><jtitle>International journal of advanced computer science & applications</jtitle><date>2018</date><risdate>2018</risdate><volume>9</volume><issue>12</issue><issn>2158-107X</issn><eissn>2156-5570</eissn><abstract>Features are normally modelled based on color, texture and shape. However, some features may have different constraints based on types, styles and pattern of an image. The Arabic subword handwriting, for example, cannot be recognized by color and not suitable to be characterized based on texture. Therefore, features based on shape are suitable to be used for recognizing Arabic subword handwriting since each of the character has various characteristics such as diacritics, thinning and strokes. These characteristics can contribute to particular a shape that is unique and can represent Arabic subword handwriting. Currently, geometry shape such as triangle has been adopted to extract useful features based on triangle properties without implicating any triangle form. In order to increase classification accuracy, these properties have been categorized into several zones where the number of features produced is directly proportional to the number of zones. Nevertheless, shape representation does not implicate any triangle properties such as ratio of side, angle and gradient. By using shape representation, it helps in reducing the number of features. Thus, this paper presents feature based on triangle shape that can represent the identity of Arabic subword handwriting. The method based on triangle shape identifies three main coordinates of triangle formed based on selected centroids. The AHDB dataset is used as a testing data. The Support Vector Machine (SVM) and Random Forest (RF), respectively were used to measure the accuracy of the proposed method using triangle shape as a feature. The accuracy results have shown better outcome with 77.65% (SVM) and 76.43% (RF), which prove the feature based on triangle shape is applicable for Arabic subword handwriting recognition.</abstract><cop>West Yorkshire</cop><pub>Science and Information (SAI) Organization Limited</pub><doi>10.14569/IJACSA.2018.091224</doi><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Centroids Color Feature extraction Handwriting Handwriting recognition Object recognition Representations Support vector machines Texture recognition Triangles |
title | Triangle Shape Feature based on Selected Centroid for Arabic Subword Handwriting |
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