{"id":"https://openalex.org/W4413205379","doi":"https://doi.org/10.1109/iccai66501.2025.00036","title":"A Machine Learning-Based Calligraphy Font Recognition System Using HOG Features and Support Vector Machine","display_name":"A Machine Learning-Based Calligraphy Font Recognition System Using HOG Features and Support Vector Machine","publication_year":2025,"publication_date":"2025-03-28","ids":{"openalex":"https://openalex.org/W4413205379","doi":"https://doi.org/10.1109/iccai66501.2025.00036"},"language":"en","primary_location":{"id":"doi:10.1109/iccai66501.2025.00036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccai66501.2025.00036","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 11th International Conference on Computing and Artificial Intelligence (ICCAI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100568646","display_name":"Chenfei Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chenfei Xu","raw_affiliation_strings":["Shanghai Normal University,Tianhua College AI School,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Normal University,Tianhua College AI School,Shanghai,China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007737263","display_name":"Jingxin Liang","orcid":"https://orcid.org/0009-0000-3883-7760"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingxin Liang","raw_affiliation_strings":["Shanghai Normal University,Tianhua College AI School,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Normal University,Tianhua College AI School,Shanghai,China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086015675","display_name":"Xufeng Ling","orcid":"https://orcid.org/0000-0001-5217-3614"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xufeng Ling","raw_affiliation_strings":["Shanghai Normal University,Tianhua College AI School,Shanghai,China"],"affiliations":[{"raw_affiliation_string":"Shanghai Normal University,Tianhua College AI School,Shanghai,China","institution_ids":["https://openalex.org/I21945476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100568646"],"corresponding_institution_ids":["https://openalex.org/I21945476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24728344,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"175","last_page":"180"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/font","display_name":"Font","score":0.8632127642631531},{"id":"https://openalex.org/keywords/calligraphy","display_name":"Calligraphy","score":0.8599452972412109},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.765198826789856},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6990500092506409},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6914592981338501},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4873805642127991},{"id":"https://openalex.org/keywords/kanji","display_name":"Kanji","score":0.4238625168800354},{"id":"https://openalex.org/keywords/chinese-characters","display_name":"Chinese characters","score":0.2020348310470581},{"id":"https://openalex.org/keywords/painting","display_name":"Painting","score":0.07252499461174011}],"concepts":[{"id":"https://openalex.org/C2777737414","wikidata":"https://www.wikidata.org/wiki/Q4868296","display_name":"Font","level":2,"score":0.8632127642631531},{"id":"https://openalex.org/C526940114","wikidata":"https://www.wikidata.org/wiki/Q12681","display_name":"Calligraphy","level":3,"score":0.8599452972412109},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.765198826789856},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6990500092506409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6914592981338501},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4873805642127991},{"id":"https://openalex.org/C83535845","wikidata":"https://www.wikidata.org/wiki/Q82772","display_name":"Kanji","level":3,"score":0.4238625168800354},{"id":"https://openalex.org/C2781051154","wikidata":"https://www.wikidata.org/wiki/Q8201","display_name":"Chinese characters","level":2,"score":0.2020348310470581},{"id":"https://openalex.org/C205783811","wikidata":"https://www.wikidata.org/wiki/Q11629","display_name":"Painting","level":2,"score":0.07252499461174011},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccai66501.2025.00036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccai66501.2025.00036","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 11th International Conference on Computing and Artificial Intelligence (ICCAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6299999952316284,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2145023731","https://openalex.org/W2158001550","https://openalex.org/W2161969291","https://openalex.org/W2326140143","https://openalex.org/W2328965991","https://openalex.org/W4239510810"],"related_works":["https://openalex.org/W2368991273","https://openalex.org/W3132096423","https://openalex.org/W2391960051","https://openalex.org/W2389028006","https://openalex.org/W4318827931","https://openalex.org/W2386906843","https://openalex.org/W391620190","https://openalex.org/W2384857662","https://openalex.org/W3037501722","https://openalex.org/W2369663100"],"abstract_inverted_index":{"This":[0],"study":[1],"presents":[2],"an":[3],"automatic":[4,61,118],"calligraphy":[5,35,68,119],"font":[6],"recognition":[7,62,103],"system":[8,59,113],"based":[9],"on":[10],"Histogram":[11],"of":[12,34,65,84,105],"Oriented":[13],"Gradients":[14],"(HOG)":[15],"feature":[16,53],"extraction":[17,54],"and":[18,31,40,63,78,132],"Support":[19],"Vector":[20],"Machine":[21],"(SVM)":[22],"classification.":[23],"Addressing":[24],"challenges":[25],"such":[26],"as":[27],"limited":[28],"data":[29,48],"resources":[30],"the":[32,58,93,97,111,126],"complexity":[33],"scripts,":[36],"morphological":[37],"image":[38],"preprocessing":[39],"Canny":[41],"edge":[42],"detection":[43],"techniques":[44],"were":[45],"applied":[46],"for":[47,117],"preprocessing.":[49],"By":[50],"integrating":[51],"HOG":[52],"with":[55,87,100],"SVM":[56,85],"classification,":[57,121],"achieved":[60,96],"classification":[64],"five":[66],"common":[67],"scripts:":[69],"Seal":[70],"Script,":[71,73,75,77],"Clerical":[72],"Cursive":[74],"Running":[76],"Regular":[79],"Script.":[80],"A":[81],"comparative":[82],"analysis":[83],"models":[86],"different":[88],"kernel":[89,95],"functions":[90],"revealed":[91],"that":[92,110],"polynomial":[94],"best":[98],"performance":[99],"a":[101],"maximum":[102],"accuracy":[104],"82.66%.":[106],"Experimental":[107],"results":[108],"demonstrate":[109],"proposed":[112],"is":[114,129],"highly":[115],"practical":[116],"script":[120,127],"particularly":[122],"in":[123],"scenarios":[124],"where":[125],"structure":[128],"relatively":[130],"simple":[131],"its":[133],"features":[134],"are":[135],"easily":[136],"extractable.":[137]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}