IEEE Trans Image Process - Adaptive fingerprint image enhancement with emphasis on preprocessing of data.

Tópicos

{ imag(1947) propos(1133) code(1026) }
{ imag(2830) propos(1344) filter(1198) }
{ method(1557) propos(1049) approach(1037) }
{ extract(1171) text(1153) clinic(932) }
{ method(1219) similar(1157) match(930) }
{ analysi(2126) use(1163) compon(1037) }
{ system(1976) rule(880) can(841) }
{ featur(1941) imag(1645) propos(1176) }
{ perform(999) metric(946) measur(919) }
{ signal(2180) analysi(812) frequenc(800) }
{ activ(1138) subject(705) human(624) }
{ model(3404) distribut(989) bayesian(671) }
{ search(2224) databas(1162) retriev(909) }
{ perform(1367) use(1326) method(1137) }
{ patient(1821) servic(1111) care(1106) }
{ estim(2440) model(1874) function(577) }
{ measur(2081) correl(1212) valu(896) }
{ data(1714) softwar(1251) tool(1186) }
{ data(3963) clinic(1234) research(1004) }
{ compound(1573) activ(1297) structur(1058) }
{ model(3480) simul(1196) paramet(876) }
{ model(2656) set(1616) predict(1553) }
{ medic(1828) order(1363) alert(1069) }
{ group(2977) signific(1463) compar(1072) }
{ first(2504) two(1366) second(1323) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ high(1669) rate(1365) level(1280) }
{ can(774) often(719) complex(702) }
{ data(1737) use(1416) pattern(1282) }
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{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
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{ learn(2355) train(1041) set(1003) }
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{ clinic(1479) use(1117) guidelin(835) }
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{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
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{ system(1050) medic(1026) inform(1018) }
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{ visual(1396) interact(850) tool(830) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
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{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ cost(1906) reduc(1198) effect(832) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ can(981) present(881) function(850) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
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{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are: 1) preprocessing; 2) global analysis; 3) local analysis; and 4) matched filtering. In the preprocessing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated toward the NIST developed NBIS software for fingerprint recognition on FVC databases.

Resumo Limpo

articl propos sever improv adapt fingerprint enhanc method base contextu filter term adapt impli paramet method automat adjust base input fingerprint imag five process block compris adapt fingerprint enhanc method four block updat propos system henc propos overal system novel four updat process block preprocess global analysi local analysi match filter preprocess local analysi block nonlinear dynam rang adjust method use global analysi match filter block differ form order statist filter appli process block yield improv new adapt fingerprint imag process method perform updat process block present evalu part paper algorithm evalu toward nist develop nbis softwar fingerprint recognit fvc databas

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