{"id":"https://openalex.org/W3143987769","doi":"https://doi.org/10.1109/icsmc.2009.5346007","title":"Zone-based hybrid feature extraction algorithm for handwritten numeral recognition of four Indian scripts","display_name":"Zone-based hybrid feature extraction algorithm for handwritten numeral recognition of four Indian scripts","publication_year":2009,"publication_date":"2009-10-01","ids":{"openalex":"https://openalex.org/W3143987769","doi":"https://doi.org/10.1109/icsmc.2009.5346007","mag":"3143987769"},"language":"en","primary_location":{"id":"doi:10.1109/icsmc.2009.5346007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2009.5346007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Systems, Man and Cybernetics","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/A5041811845","display_name":"S. V. Rajashekararadhya","orcid":null},"institutions":[{"id":"https://openalex.org/I33585257","display_name":"Anna University, Chennai","ror":"https://ror.org/01qhf1r47","country_code":"IN","type":"education","lineage":["https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"S.V. Rajashekararadhya","raw_affiliation_strings":["Department of Electrical Engineering, CEG, Anna University, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, CEG, Anna University, Chennai, India","institution_ids":["https://openalex.org/I33585257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108229602","display_name":"Vanaja Ranjan","orcid":null},"institutions":[{"id":"https://openalex.org/I33585257","display_name":"Anna University, Chennai","ror":"https://ror.org/01qhf1r47","country_code":"IN","type":"education","lineage":["https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vanaja P Ranjan","raw_affiliation_strings":["Department of Electrical Engineering, CEG, Anna University, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, CEG, Anna University, Chennai, India","institution_ids":["https://openalex.org/I33585257"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041811845"],"corresponding_institution_ids":["https://openalex.org/I33585257"],"apc_list":null,"apc_paid":null,"fwci":0.6471,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.75710801,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"4815","issue":null,"first_page":"5145","last_page":"5150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":1.0,"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":1.0,"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":0.9948999881744385,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.991599977016449,"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/centroid","display_name":"Centroid","score":0.7452336549758911},{"id":"https://openalex.org/keywords/numeral-system","display_name":"Numeral system","score":0.7256964445114136},{"id":"https://openalex.org/keywords/malayalam","display_name":"Malayalam","score":0.6999326348304749},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6662024855613708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6249504685401917},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5955522656440735},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5792446732521057},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5747460722923279},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5584666728973389},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5263888835906982},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5097641348838806},{"id":"https://openalex.org/keywords/character","display_name":"Character (mathematics)","score":0.501819372177124},{"id":"https://openalex.org/keywords/telugu","display_name":"Telugu","score":0.4612419009208679},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.42567890882492065},{"id":"https://openalex.org/keywords/kannada","display_name":"Kannada","score":0.4201869070529938},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31215885281562805}],"concepts":[{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.7452336549758911},{"id":"https://openalex.org/C204160518","wikidata":"https://www.wikidata.org/wiki/Q122653","display_name":"Numeral system","level":2,"score":0.7256964445114136},{"id":"https://openalex.org/C2779662586","wikidata":"https://www.wikidata.org/wiki/Q36236","display_name":"Malayalam","level":2,"score":0.6999326348304749},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6662024855613708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6249504685401917},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5955522656440735},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5792446732521057},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5747460722923279},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5584666728973389},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5263888835906982},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5097641348838806},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.501819372177124},{"id":"https://openalex.org/C2778756302","wikidata":"https://www.wikidata.org/wiki/Q8097","display_name":"Telugu","level":2,"score":0.4612419009208679},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.42567890882492065},{"id":"https://openalex.org/C2778579358","wikidata":"https://www.wikidata.org/wiki/Q33673","display_name":"Kannada","level":2,"score":0.4201869070529938},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31215885281562805},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsmc.2009.5346007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsmc.2009.5346007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Systems, Man and Cybernetics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1919867394","https://openalex.org/W1996709837","https://openalex.org/W2017787659","https://openalex.org/W2034458753","https://openalex.org/W2044943596","https://openalex.org/W2100544284","https://openalex.org/W2110903505","https://openalex.org/W2118924867","https://openalex.org/W2132043281","https://openalex.org/W2138270545","https://openalex.org/W2142069714","https://openalex.org/W2148603752","https://openalex.org/W2162403778","https://openalex.org/W2171927392","https://openalex.org/W4230674625"],"related_works":["https://openalex.org/W2336974148","https://openalex.org/W2146076056","https://openalex.org/W2345184372","https://openalex.org/W2732882768","https://openalex.org/W203536286","https://openalex.org/W4211111701","https://openalex.org/W2546942002","https://openalex.org/W2791932178","https://openalex.org/W2402952899","https://openalex.org/W2129300691"],"abstract_inverted_index":{"India":[0],"is":[1,34,40,61,69,88,94,126],"a":[2,25],"multi-lingual":[3],"and":[4,13,36,137,147,157,166],"multi-script":[5],"country,":[6],"where":[7],"eighteen":[8],"official":[9],"scripts":[10],"are":[11,15,112,132,142],"accepted":[12],"there":[14],"over":[16],"hundred":[17],"regional":[18],"languages.":[19],"In":[20],"this":[21],"paper":[22],"we":[23],"propose":[24],"zone-based":[26],"hybrid":[27],"feature":[28,124],"extraction":[29],"system.":[30],"The":[31,74,134],"character":[32,52],"centroid":[33,53,68,80],"computed":[35,62,71,89],"the":[37,51,55,59,66,78,82,86,99,103,115,123],"image":[38,121],"(character/numeral)":[39],"further":[41],"divided":[42],"into":[43],"n":[44],"equal":[45],"zones.":[46],"An":[47],"average":[48,75],"angle":[49,76],"from":[50,77],"to":[54,81],"pixels":[56,83],"present":[57,84,101],"in":[58,85,102,122],"zone,":[60],"(one":[63,90],"feature).":[64,91],"Similarly,":[65],"zone":[67,79,87,120],"also":[70],"(two":[72],"features).":[73],"This":[92],"procedure":[93],"sequentially":[95],"repeated":[96],"for":[97,144,162],"all":[98],"zones/grids/boxes":[100],"numeral":[104],"image.":[105],"There":[106],"could":[107],"be":[108],"some":[109],"zones":[110],"that":[111,118],"empty;":[113],"then,":[114],"value":[116],"of":[117],"particular":[119],"vector":[125,139,172],"zero.":[127],"Finally,":[128],"4\u00d7n":[129],"such":[130],"features":[131],"extracted.":[133],"nearest":[135],"neighbor":[136],"support":[138,171],"machine":[140],"classifiers":[141],"used":[143],"subsequent":[145],"classification":[146],"recognition":[148,160],"purposes.":[149],"We":[150],"obtained":[151],"97.85":[152],"%,":[153,155],"96.8":[154],"95.1%":[156],"95":[158],"%":[159],"rates":[161],"Kannada,":[163],"Telugu,":[164],"Tamil":[165],"Malayalam":[167],"numerals":[168],"respectively,":[169],"using":[170],"machine.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}