{"id":"https://openalex.org/W7119481789","doi":"https://doi.org/10.1145/3774521.3774539","title":"Unveiling Text in Challenging Stone Inscriptions: A Character-Context-Aware Patching Strategy for Binarization","display_name":"Unveiling Text in Challenging Stone Inscriptions: A Character-Context-Aware Patching Strategy for Binarization","publication_year":2025,"publication_date":"2025-12-17","ids":{"openalex":"https://openalex.org/W7119481789","doi":"https://doi.org/10.1145/3774521.3774539"},"language":null,"primary_location":{"id":"doi:10.1145/3774521.3774539","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774521.3774539","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteen Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774521.3774539","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5122323075","display_name":"Pratyush Jena","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pratyush Jena","raw_affiliation_strings":["IIIT Hyderabad, Hyderabad, India"],"raw_orcid":"https://orcid.org/0009-0009-7681-7977","affiliations":[{"raw_affiliation_string":"IIIT Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031703448","display_name":"Amal Joseph","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Amal Joseph","raw_affiliation_strings":["IIIT Hyderabad, Hyderabad, India"],"raw_orcid":"https://orcid.org/0009-0005-3466-5558","affiliations":[{"raw_affiliation_string":"IIIT Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122397008","display_name":"Arnav Sharma","orcid":null},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arnav Sharma","raw_affiliation_strings":["IIIT Hyderabad, Hyderabad, India"],"raw_orcid":"https://orcid.org/0009-0001-8367-8639","affiliations":[{"raw_affiliation_string":"IIIT Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038936106","display_name":"Ravi Kiran Sarvadevabhatla","orcid":"https://orcid.org/0000-0003-4134-1154"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ravi Kiran Sarvadevabhatla","raw_affiliation_strings":["IIIT Hyderabad, Hyderabad, India"],"raw_orcid":"https://orcid.org/0000-0003-4134-1154","affiliations":[{"raw_affiliation_string":"IIIT Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I65181880"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55833895,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.8592000007629395,"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":0.8592000007629395,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.08789999783039093,"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":0.005400000140070915,"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/robustness","display_name":"Robustness (evolution)","score":0.7038000226020813},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6072999835014343},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5442000031471252},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4562000036239624},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4293999969959259},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4214000105857849},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3822000026702881},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3465000092983246}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7846999764442444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7297000288963318},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7038000226020813},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6072999835014343},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5442000031471252},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47519999742507935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4562000036239624},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4293999969959259},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4214000105857849},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3822000026702881},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3465000092983246},{"id":"https://openalex.org/C2987247673","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Character recognition","level":3,"score":0.3418999910354614},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3197999894618988},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C2983812711","wikidata":"https://www.wikidata.org/wiki/Q167555","display_name":"Text recognition","level":3,"score":0.28139999508857727},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2671000063419342},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C2986577269","wikidata":"https://www.wikidata.org/wiki/Q11306265","display_name":"Random noise","level":2,"score":0.26190000772476196}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3774521.3774539","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774521.3774539","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteen Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2601.03609","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.03609","pdf_url":"https://arxiv.org/pdf/2601.03609","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3774521.3774539","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774521.3774539","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteen Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Binarization":[0],"is":[1],"a":[2,81,141],"popular":[3],"first":[4],"step":[5],"towards":[6],"text":[7,39,68,221],"extraction":[8],"in":[9,77],"historical":[10,220],"artifacts.":[11],"Stone":[12],"inscription":[13,204],"images":[14],"pose":[15],"severe":[16],"challenges":[17],"for":[18,104,211],"binarization":[19,48,73,163],"due":[20],"to":[21,50,54,66,87,99,112,131,185],"poor":[22],"contrast":[23],"between":[24],"etched":[25],"characters":[26],"and":[27,36,41,52,71,83,122,135,167,188,194,219],"the":[28,62,110,128,151,209],"stone":[29,148],"background,":[30],"non-uniform":[31],"surface":[32,133],"degradation,":[33],"distracting":[34],"artifacts,":[35],"highly":[37],"variable":[38],"density":[40],"layouts.":[42],"These":[43],"conditions":[44],"frequently":[45],"cause":[46],"existing":[47],"techniques":[49],"fail":[51],"struggle":[53],"isolate":[55],"coherent":[56],"character":[57],"regions.":[58],"Many":[59],"approaches":[60],"sub-divide":[61],"image":[63],"into":[64],"patches":[65,93],"improve":[67,72],"fragment":[69],"resolution":[70],"performance.":[74],"With":[75],"this":[76],"mind,":[78],"we":[79],"present":[80],"robust":[82],"adaptive":[84],"patching":[85,159],"strategy":[86],"binarize":[88],"challenging":[89],"Indic":[90,147,177,187],"inscriptions.":[91],"The":[92,106],"from":[94],"our":[95,119,157,179,206],"approach":[96],"are":[97],"used":[98],"train":[100],"an":[101],"Attention":[102],"U-Net":[103],"binarization.":[105],"attention":[107],"mechanism":[108,160],"allows":[109],"model":[111,129,180],"focus":[113],"on":[114,174],"subtle":[115],"structural":[116],"cues,":[117],"while":[118],"dynamic":[120],"sampling":[121],"patch":[123],"selection":[124],"method":[125,207],"ensures":[126],"that":[127,156],"learns":[130],"overcome":[132],"noise":[134],"layout":[136],"irregularities.":[137],"We":[138,154],"also":[139],"introduce":[140],"carefully":[142],"annotated,":[143],"pixel-precise":[144],"dataset":[145],"of":[146,203],"inscriptions":[149],"at":[150],"character-fragment":[152],"level.":[153],"demonstrate":[155],"novel":[158],"significantly":[161],"boosts":[162],"performance":[164],"across":[165],"classical":[166],"deep":[168],"learning":[169],"baselines.":[170],"Despite":[171],"training":[172],"only":[173],"single":[175],"script":[176,216],"dataset,":[178],"exhibits":[181],"strong":[182],"zero-shot":[183],"generalization":[184,196],"other":[186],"non-indic":[189],"scripts,":[190],"highlighting":[191],"its":[192],"robustness":[193],"script-agnostic":[195],"capabilities.":[197],"By":[198],"producing":[199],"clean,":[200],"structured":[201],"representations":[202],"content,":[205],"lays":[208],"foundation":[210],"downstream":[212],"tasks":[213],"such":[214],"as":[215],"identification,":[217],"OCR,":[218],"analysis.":[222],"Project":[223],"page:":[224],"https://ihdia.iiit.ac.in/shilalekhya-binarization/":[225]},"counts_by_year":[],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2026-01-09T00:00:00"}