{"id":"https://openalex.org/W2422879858","doi":"https://doi.org/10.1109/ncvpripg.2015.7489996","title":"Histogram of Radon Projections: A new descriptor for object detection","display_name":"Histogram of Radon Projections: A new descriptor for object detection","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2422879858","doi":"https://doi.org/10.1109/ncvpripg.2015.7489996","mag":"2422879858"},"language":"en","primary_location":{"id":"doi:10.1109/ncvpripg.2015.7489996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncvpripg.2015.7489996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","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/A5090614932","display_name":"Soorya S. Kumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Soorya S. Kumar","raw_affiliation_strings":["College of Engineering, Trivandrum"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Trivandrum","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015246485","display_name":"C. V. Jiji","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiji C.V.","raw_affiliation_strings":["College of Engineering, Trivandrum"],"affiliations":[{"raw_affiliation_string":"College of Engineering, Trivandrum","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5090614932"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.22151687,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"24","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval 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/T10627","display_name":"Advanced Image and Video Retrieval 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/T10036","display_name":"Advanced Neural Network Applications","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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.998199999332428,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8243043422698975},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.7341943383216858},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7191768288612366},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.604993462562561},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6040935516357422},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5753599405288696},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5512715578079224},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.5500631332397461},{"id":"https://openalex.org/keywords/radon-transform","display_name":"Radon transform","score":0.5429761409759521},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.5366864204406738},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5056703090667725},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49413374066352844},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4339507818222046},{"id":"https://openalex.org/keywords/radon","display_name":"Radon","score":0.4191751480102539},{"id":"https://openalex.org/keywords/bin","display_name":"Bin","score":0.4148729145526886},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3176165819168091},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29725056886672974},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.08863997459411621}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8243043422698975},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7341943383216858},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7191768288612366},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.604993462562561},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6040935516357422},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5753599405288696},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5512715578079224},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.5500631332397461},{"id":"https://openalex.org/C197231052","wikidata":"https://www.wikidata.org/wiki/Q979829","display_name":"Radon transform","level":2,"score":0.5429761409759521},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.5366864204406738},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5056703090667725},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49413374066352844},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4339507818222046},{"id":"https://openalex.org/C545943180","wikidata":"https://www.wikidata.org/wiki/Q1133","display_name":"Radon","level":2,"score":0.4191751480102539},{"id":"https://openalex.org/C156273044","wikidata":"https://www.wikidata.org/wiki/Q4913766","display_name":"Bin","level":2,"score":0.4148729145526886},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3176165819168091},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29725056886672974},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.08863997459411621},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ncvpripg.2015.7489996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncvpripg.2015.7489996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W153848781","https://openalex.org/W1489191866","https://openalex.org/W1580045085","https://openalex.org/W1608462934","https://openalex.org/W1993605889","https://openalex.org/W2012330712","https://openalex.org/W2031454541","https://openalex.org/W2064177156","https://openalex.org/W2066941820","https://openalex.org/W2082256640","https://openalex.org/W2153635508","https://openalex.org/W2159686933","https://openalex.org/W2161106546","https://openalex.org/W2161969291","https://openalex.org/W2163389987","https://openalex.org/W2168356304","https://openalex.org/W2217896605","https://openalex.org/W2482655587","https://openalex.org/W4252079569","https://openalex.org/W6683411478","https://openalex.org/W6997266731"],"related_works":["https://openalex.org/W2107701374","https://openalex.org/W1616588898","https://openalex.org/W1964258184","https://openalex.org/W4249504934","https://openalex.org/W2183416055","https://openalex.org/W2063115400","https://openalex.org/W2040034980","https://openalex.org/W2568867011","https://openalex.org/W4387676042","https://openalex.org/W2370380226"],"abstract_inverted_index":{"One":[0],"of":[1,13,55,127,134],"the":[2,21,25,34,37,53,64,76,106,141],"important":[3],"requirements":[4],"for":[5,49,73,82,88,113,146],"a":[6,11,45],"good":[7],"object":[8,27,50],"detector":[9],"is":[10,66,130,138],"set":[12,48],"robust":[14],"visual":[15],"features.":[16],"These":[17,96],"features":[18],"extracted":[19],"from":[20,36],"reference":[22],"images":[23,118],"containing":[24],"desired":[26],"instance":[28],"will":[29],"be":[30],"used":[31],"to":[32,104],"identify":[33],"objects":[35],"test":[38],"images.":[39,124,151],"In":[40],"this":[41,61,111,128],"paper,":[42],"we":[43],"propose":[44],"new":[46,142],"feature":[47,62],"detection,":[51],"called":[52],"Histogram":[54],"Radon":[56,77],"Projections":[57],"(HRP).":[58],"To":[59],"compute":[60],"descriptor,":[63],"image":[65],"first":[67],"divided":[68],"into":[69,94],"smaller":[70],"cells":[71],"and":[72,85,101,119,136,149],"each":[74,89],"cell,":[75],"transform":[78,90],"values":[79,98],"are":[80,92,99],"calculated":[81],"different":[83],"orientations":[84],"weighted":[86],"votes":[87],"coefficient":[91],"accumulated":[93],"bins.":[95],"bin":[97],"block-normalized":[100],"collected":[102],"together":[103],"get":[105],"final":[107],"descriptor.":[108],"We":[109],"use":[110],"descriptor":[112,129,143],"car":[114],"detection":[115,121],"using":[116,122],"gray-scale":[117,148],"pedestrian":[120],"RGB":[123,150],"The":[125],"performance":[126],"compared":[131],"with":[132],"that":[133,140],"HOG":[135],"it":[137],"found":[139],"performs":[144],"better":[145],"both":[147]},"counts_by_year":[{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
