{"id":"https://openalex.org/W2591913650","doi":"https://doi.org/10.1109/icdsp.2016.7868642","title":"Incorporating negentropy in saliency-based search free car number plate localization","display_name":"Incorporating negentropy in saliency-based search free car number plate localization","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2591913650","doi":"https://doi.org/10.1109/icdsp.2016.7868642","mag":"2591913650"},"language":"en","primary_location":{"id":"doi:10.1109/icdsp.2016.7868642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2016.7868642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Digital Signal Processing (DSP)","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/A5103233205","display_name":"Amin Safaei","orcid":"https://orcid.org/0000-0003-4789-2379"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Amin Safaei","raw_affiliation_strings":["Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, United Kingdom","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103218410","display_name":"Hongying Tang","orcid":"https://orcid.org/0000-0003-2534-737X"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hongying L. Tang","raw_affiliation_strings":["Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, United Kingdom","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004587843","display_name":"Saeid Sanei","orcid":"https://orcid.org/0000-0002-1446-5744"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Saeid Sanei","raw_affiliation_strings":["Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, United Kingdom","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5103233205"],"corresponding_institution_ids":["https://openalex.org/I28290843"],"apc_list":null,"apc_paid":null,"fwci":0.3274,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.69881347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"18","issue":null,"first_page":"667","last_page":"671"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12707","display_name":"Vehicle License Plate Recognition","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9869999885559082,"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":0.9842000007629395,"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/negentropy","display_name":"Negentropy","score":0.9467473030090332},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6768608689308167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6405361294746399},{"id":"https://openalex.org/keywords/license","display_name":"License","score":0.5925339460372925},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5181799530982971},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.5149146318435669},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49309560656547546},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49208587408065796},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.47566694021224976},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.45908868312835693},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4532895088195801},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4338741898536682},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.4196772277355194},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2418433427810669},{"id":"https://openalex.org/keywords/independent-component-analysis","display_name":"Independent component analysis","score":0.14976024627685547},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13911092281341553}],"concepts":[{"id":"https://openalex.org/C118346863","wikidata":"https://www.wikidata.org/wiki/Q252552","display_name":"Negentropy","level":3,"score":0.9467473030090332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6768608689308167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6405361294746399},{"id":"https://openalex.org/C2780560020","wikidata":"https://www.wikidata.org/wiki/Q79719","display_name":"License","level":2,"score":0.5925339460372925},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5181799530982971},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.5149146318435669},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49309560656547546},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49208587408065796},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.47566694021224976},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.45908868312835693},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4532895088195801},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4338741898536682},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.4196772277355194},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2418433427810669},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.14976024627685547},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13911092281341553},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icdsp.2016.7868642","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdsp.2016.7868642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Digital Signal Processing (DSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:irep.ntu.ac.uk:34435","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400559","display_name":"Nottingham Trent University's Institutional Repository (Nottingham Trent Repository)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I52590639","host_organization_name":"Nottingham Trent University","host_organization_lineage":["https://openalex.org/I52590639"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Book Section"},{"id":"mag:2753492672","is_oa":false,"landing_page_url":"http://jglobal.jst.go.jp/en/public/20090422/201702278209037779","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1599826403","https://openalex.org/W1978530503","https://openalex.org/W1981027822","https://openalex.org/W1990455919","https://openalex.org/W2044994774","https://openalex.org/W2064804280","https://openalex.org/W2104913567","https://openalex.org/W2128272608","https://openalex.org/W2171786422","https://openalex.org/W2243843718","https://openalex.org/W2253220722","https://openalex.org/W2293399436","https://openalex.org/W2396616477","https://openalex.org/W2400992426","https://openalex.org/W2468231413","https://openalex.org/W2546165430","https://openalex.org/W6666882698","https://openalex.org/W6996427754"],"related_works":["https://openalex.org/W2767731115","https://openalex.org/W1998105760","https://openalex.org/W1972811221","https://openalex.org/W2049202975","https://openalex.org/W2046551244","https://openalex.org/W355849711","https://openalex.org/W2102824076","https://openalex.org/W3014800566","https://openalex.org/W1967538711","https://openalex.org/W426326770"],"abstract_inverted_index":{"License":[0],"plate":[1],"localization":[2],"algorithms":[3],"aim":[4],"to":[5,57,114],"detect":[6],"license":[7,43],"plates":[8,44],"within":[9],"the":[10,21,27,41,46,49,53,59,94,98,107],"scene.":[11],"In":[12],"this":[13],"paper,":[14],"a":[15,54],"new":[16],"algorithm":[17,67],"is":[18,112],"discussed":[19],"where":[20],"necessary":[22],"conditions":[23],"are":[24,97],"imposed":[25],"into":[26],"saliency":[28],"detection":[29,81],"equations.":[30],"Measures":[31],"of":[32,75,83,90,106],"distance":[33],"between":[34],"probability":[35,61],"distributions":[36],"such":[37],"as":[38],"negentropy":[39],"finds":[40],"candidate":[42],"in":[45,116],"image":[47],"and":[48,77,85,110],"Bayesian":[50],"methodology":[51],"exploits":[52],"priori":[55],"information":[56],"estimate":[58],"highest":[60],"for":[62,71,93],"each":[63],"candidate.":[64],"The":[65,101],"proposed":[66,102],"has":[68],"been":[69],"tested":[70],"three":[72],"datasets,":[73],"consisting":[74],"gray-scale":[76],"color":[78],"images.":[79],"A":[80],"accuracy":[82],"96%":[84],"an":[86],"average":[87],"execution":[88],"time":[89],"80":[91],"ms":[92],"first":[95],"dataset":[96],"marked":[99],"outcomes.":[100],"method":[103],"outperforms":[104],"most":[105],"state-of-the-art":[108],"techniques":[109],"it":[111],"suitable":[113],"use":[115],"real-time":[117],"ALPR":[118],"applications.":[119]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}