{"id":"https://openalex.org/W3158561295","doi":"https://doi.org/10.1109/icpr48806.2021.9412534","title":"Local Gradient Difference Features for Classification of 2D-3D Natural Scene Text Images","display_name":"Local Gradient Difference Features for Classification of 2D-3D Natural Scene Text Images","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3158561295","doi":"https://doi.org/10.1109/icpr48806.2021.9412534","mag":"3158561295"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412534","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412534","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5033782598","display_name":"Lokesh Nandanwar","orcid":"https://orcid.org/0000-0001-7201-0855"},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Lokesh Nandanwar","raw_affiliation_strings":["Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia","institution_ids":["https://openalex.org/I33849332"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025871978","display_name":"Palaiahnakote Shivakumara","orcid":"https://orcid.org/0000-0001-9026-4613"},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Palaiahnakote Shivakumara","raw_affiliation_strings":["Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia","institution_ids":["https://openalex.org/I33849332"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073391891","display_name":"Raghavendra Ramachandra","orcid":"https://orcid.org/0000-0003-0484-3956"},"institutions":[{"id":"https://openalex.org/I204778367","display_name":"Norwegian University of Science and Technology","ror":"https://ror.org/05xg72x27","country_code":"NO","type":"education","lineage":["https://openalex.org/I204778367"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Ramachandra Raghavendra","raw_affiliation_strings":["Faculty of Information Technology and Electrical Engineering, IIK, NTNU, Norway"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology and Electrical Engineering, IIK, NTNU, Norway","institution_ids":["https://openalex.org/I204778367"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061696740","display_name":"Tong L\u00fc","orcid":"https://orcid.org/0000-0002-7051-5347"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Lu","raw_affiliation_strings":["National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Lab for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068803496","display_name":"Umapada Pal","orcid":"https://orcid.org/0000-0002-5426-2618"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Umapada Pal","raw_affiliation_strings":["Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088217927","display_name":"Daniel Lopresti","orcid":"https://orcid.org/0000-0003-2129-4223"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Lopresti","raw_affiliation_strings":["Computer Science & Engineering, Lehigh University, Bethlehem, PA, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science & Engineering, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047447489","display_name":"Nor Badrul Anuar","orcid":"https://orcid.org/0000-0003-4380-5303"},"institutions":[{"id":"https://openalex.org/I33849332","display_name":"University of Malaya","ror":"https://ror.org/00rzspn62","country_code":"MY","type":"education","lineage":["https://openalex.org/I33849332"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Nor Badrul Anuar","raw_affiliation_strings":["Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur, Malaysia","institution_ids":["https://openalex.org/I33849332"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5033782598"],"corresponding_institution_ids":["https://openalex.org/I33849332"],"apc_list":null,"apc_paid":null,"fwci":0.3843,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59284314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1112","last_page":"1119"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9965000152587891,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9937999844551086,"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/computer-science","display_name":"Computer science","score":0.7580629587173462},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7546669840812683},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7533952593803406},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.69253009557724},{"id":"https://openalex.org/keywords/text-detection","display_name":"Text detection","score":0.6381825804710388},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5577634572982788},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45914599299430847},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44701212644577026},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39187106490135193}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7580629587173462},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7546669840812683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7533952593803406},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.69253009557724},{"id":"https://openalex.org/C2983589003","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text detection","level":3,"score":0.6381825804710388},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5577634572982788},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45914599299430847},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44701212644577026},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39187106490135193}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412534","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412534","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W243301038","https://openalex.org/W839678207","https://openalex.org/W1522301498","https://openalex.org/W1822742915","https://openalex.org/W2041004593","https://openalex.org/W2510034651","https://openalex.org/W2522010881","https://openalex.org/W2523246573","https://openalex.org/W2606394513","https://openalex.org/W2791490164","https://openalex.org/W2810983211","https://openalex.org/W2902494497","https://openalex.org/W2918572391","https://openalex.org/W2947301138","https://openalex.org/W2963163009","https://openalex.org/W2963526661","https://openalex.org/W2963647456","https://openalex.org/W2964018263","https://openalex.org/W2964121744","https://openalex.org/W2988785208","https://openalex.org/W2989011051","https://openalex.org/W2994497769","https://openalex.org/W3002492016","https://openalex.org/W6631190155","https://openalex.org/W6638364407","https://openalex.org/W6771478058","https://openalex.org/W6863446615"],"related_works":["https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W4390494008","https://openalex.org/W2053596378","https://openalex.org/W2168523118","https://openalex.org/W2073639911","https://openalex.org/W2043988397"],"abstract_inverted_index":{"Methods":[0],"developed":[1],"for":[2,11,27,52,62,87,96,107,131],"normal":[3],"2D":[4,30,118],"text":[5,12,35,119,179,195],"detection":[6,196],"do":[7],"not":[8,163],"work":[9,146],"well":[10],"that":[13,38,183],"is":[14,85,136,187],"rendered":[15],"using":[16],"decorative,":[17],"3D":[18,32],"effects,":[19],"etc.":[20],"This":[21,99],"paper":[22],"proposes":[23],"a":[24,68,80,117,127,140,148],"new":[25,141],"method":[26,42,57,135,175,186],"classification":[28,50],"of":[29,75,92,113,172,189],"and":[31,94,180,197],"natural":[33,154],"scene":[34,155],"images":[36,177],"so":[37],"an":[39],"appropriate":[40],"recognition":[41,198],"can":[43],"be":[44],"chosen":[45],"accordingly":[46],"based":[47],"on":[48,138,176],"the":[49,72,90,109,173,184],"results":[51,171],"better":[53],"performance.":[54],"The":[55,121,133,191],"proposed":[56,134,174,185,192],"explores":[58],"local":[59],"gradient":[60],"differences":[61],"obtaining":[63],"candidate":[64,76],"pixels,":[65,77],"which":[66,84,115,161],"represent":[67],"stroke.":[69],"To":[70],"study":[71],"spatial":[73,111],"distribution":[74],"we":[78],"propose":[79],"measure,":[81],"called":[82],"COLD,":[83,114],"denser":[86],"pixels":[88],"toward":[89],"center":[91],"strokes":[93],"scattered":[95],"non-stroke":[97],"pixels.":[98],"observation":[100],"leads":[101],"us":[102],"to":[103],"introduce":[104],"mass":[105],"features":[106,123],"extracting":[108],"regular":[110],"pattern":[112],"indicates":[116],"image.":[120],"extracted":[122],"are":[124],"fed":[125],"into":[126],"Neural":[128],"Network":[129],"(NN)":[130],"classification.":[132,202],"tested":[137],"(i)":[139],"dataset":[142,150],"introduced":[143],"in":[144],"this":[145],"(ii)":[147],"second":[149],"assembled":[151],"from":[152],"standard":[153],"datasets":[156,160],"(iii)":[157],"Non-Text":[158],"Image":[159],"does":[162],"contain":[164],"text,":[165],"rather":[166],"it":[167],"contains":[168],"objects.":[169],"Experimental":[170],"with":[178],"non-text":[181],"show":[182],"independent":[188],"text.":[190],"approach":[193],"improves":[194],"performance":[199],"significantly":[200],"after":[201]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}