{"id":"https://openalex.org/W1620098806","doi":"https://doi.org/10.1109/icacci.2015.7275814","title":"Text localization in video/scene images using Kirsch Directional Masks","display_name":"Text localization in video/scene images using Kirsch Directional Masks","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W1620098806","doi":"https://doi.org/10.1109/icacci.2015.7275814","mag":"1620098806"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2015.7275814","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2015.7275814","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5015312288","display_name":"B. H. Shekar","orcid":"https://orcid.org/0000-0003-4379-2960"},"institutions":[{"id":"https://openalex.org/I19008122","display_name":"Mangalore University","ror":"https://ror.org/05fep3933","country_code":"IN","type":"education","lineage":["https://openalex.org/I19008122"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"B.H. Shekar","raw_affiliation_strings":["Mangalore University, Mangalagangotri, Karnataka, IN","[Department of Computer Science, Mangalore University, Karnataka, India]"],"affiliations":[{"raw_affiliation_string":"Mangalore University, Mangalagangotri, Karnataka, IN","institution_ids":["https://openalex.org/I19008122"]},{"raw_affiliation_string":"[Department of Computer Science, Mangalore University, Karnataka, India]","institution_ids":["https://openalex.org/I19008122"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109883825","display_name":"Smitha M.L.","orcid":null},"institutions":[{"id":"https://openalex.org/I19008122","display_name":"Mangalore University","ror":"https://ror.org/05fep3933","country_code":"IN","type":"education","lineage":["https://openalex.org/I19008122"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Smitha M.L.","raw_affiliation_strings":["Department of Computer Science, Mangalore University, Mangalore, Karnataka, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Mangalore University, Mangalore, Karnataka, India","institution_ids":["https://openalex.org/I19008122"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015312288"],"corresponding_institution_ids":["https://openalex.org/I19008122"],"apc_list":null,"apc_paid":null,"fwci":0.3682,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66545509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"2","issue":null,"first_page":"1436","last_page":"1440"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9983000159263611,"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":0.9961000084877014,"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":0.7736266851425171},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.744229793548584},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.680463433265686},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6690306067466736},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5802047848701477},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.53383868932724},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.47073614597320557},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.42593914270401},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.41530871391296387}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7736266851425171},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.744229793548584},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.680463433265686},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6690306067466736},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5802047848701477},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.53383868932724},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.47073614597320557},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.42593914270401},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.41530871391296387},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2015.7275814","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2015.7275814","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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":20,"referenced_works":["https://openalex.org/W1539258218","https://openalex.org/W1989327159","https://openalex.org/W2006408850","https://openalex.org/W2022083974","https://openalex.org/W2049574251","https://openalex.org/W2091876488","https://openalex.org/W2095469472","https://openalex.org/W2099306567","https://openalex.org/W2107996860","https://openalex.org/W2108193766","https://openalex.org/W2113751684","https://openalex.org/W2129116707","https://openalex.org/W2134378185","https://openalex.org/W2135119614","https://openalex.org/W2142082467","https://openalex.org/W2142907989","https://openalex.org/W2177274842","https://openalex.org/W6632178270","https://openalex.org/W6679915204","https://openalex.org/W6681726749"],"related_works":["https://openalex.org/W1557094818","https://openalex.org/W2183246718","https://openalex.org/W2099261052","https://openalex.org/W3209204065","https://openalex.org/W2105707930","https://openalex.org/W1755711892","https://openalex.org/W2160907113","https://openalex.org/W2080069147","https://openalex.org/W3035059915","https://openalex.org/W3034835492"],"abstract_inverted_index":{"Text":[0],"plays":[1],"its":[2,17],"vital":[3],"role":[4],"in":[5,16,139],"visual":[6],"content":[7],"analysis":[8,99],"and":[9,20,63,69,82,100,130,137,141],"understanding.":[10],"Videos":[11],"contain":[12],"text":[13,18,92,108,113],"with":[14],"diversity":[15],"patterns":[19],"complex":[21],"backgrounds.":[22],"In":[23],"this":[24],"paper,":[25],"we":[26,78],"propose":[27],"an":[28],"approach":[29],"based":[30],"on":[31,119],"compass":[32],"operator":[33],"for":[34,53,105],"detecting":[35],"the":[36,40,45,54,64,87,91,106,112,120,125],"edges.":[37],"We":[38],"obtain":[39,72],"edge":[41,65],"maps":[42,66],"by":[43],"convolving":[44],"Kirsch":[46],"Directional":[47],"Masks":[48],"along":[49],"eight":[50],"different":[51],"directions":[52],"preprocessed":[55],"video":[56],"frame.":[57],"The":[58],"resultant":[59],"images":[60],"are":[61,67,94,103],"binarized":[62,75],"analyzed":[68],"concatenated":[70],"to":[71,85],"a":[73],"single":[74],"image.":[76],"Further,":[77],"employ":[79],"geometrical":[80],"rules":[81],"shape":[83],"properties":[84],"eliminate":[86],"false":[88],"positives.":[89],"Then,":[90],"regions":[93,109],"identified":[95],"using":[96],"connected":[97],"component":[98],"bounding":[101],"boxes":[102],"placed":[104],"detected":[107],"so":[110],"that":[111,124],"gets":[114],"localized.":[115],"Experimental":[116],"results":[117],"obtained":[118],"standard":[121],"datasets":[122],"reveal":[123],"proposed":[126],"method":[127],"effectively":[128],"detect":[129],"localize":[131],"texts":[132],"of":[133],"various":[134],"sizes,":[135],"fonts":[136],"colors":[138],"videos":[140],"scene":[142],"images.":[143]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}