Patent AU-2017272288-B2 (AU)
Title: Method, system, electronic device, and medium for classifying license plates based on deep learning
Inventor: WANG JIANZONG
IPC: G06V10/764
Filed: 2017-06-23
Granted: 2019-06-13
Abstract: ( 12 )IJP 13t- f'IS t hfift4 ;f I Il P't (19)tf1`1_flV57 1t t.U1t5 IN 111111111DIDIIDIDIDIIDIIDIIID10DVIDIIIDDIII (10) W tii (43) 2017 w 12 - 28 (28.12.2017) W I P OI P C T WO2017/220032A (51) )- j j-: F J, Guangdong 518000 (CN)c 4 W(XIAO, G06K 9/62 (2006.01) Jing); + l T tfl I J $ I $ _1 M (21) p5$i--: PCT/CN2017/089875 G J, Guang g 518000 (CN)c (22)Rd p, I$ i : 2017 6 A 23 H (23.06.2017) (74){tIWA: || il i O rt (t PT (t I J1A) (SHENZHEN WORLD (25) $i9g : +A INTELLECTUAL PROPERTYAGENCY(GENERAL (26) Qigi : $f PARTNERSHIP)); + [I t T #l S iU E X N (30)Vt~y,: I M M K A IK R M 10 i+ K N1528 F (30) ft4 : MtI, Guangdong 518000 (CN)c 2016104709069 2016F6)J24 H (24.06.2016) CN (71) $ igAX:1-7 .}(I3 )) -RQ 8] PINGAN AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, TECHNOLOGY (SHENZHEN) CO.,LTD.) [CN/CN]; BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, + I'- T 1 #il is E6 E I$ 9VI A If I= M§ CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, NGuanO), Guangdong 518000 (CN)° GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, (72) & PA : ¶ 1 " (WANG, Jianzong); li 1 ST JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, M#I Is E N ff X HI4I f I KI I $ It= M $ LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, Guangdong 518000 (CN) o Ij J (LIU, Ming); MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, l -1 I 4 I IHE # f I f l9 I F I+ Y PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, (54) Title: VEHICLE LICENSE PLATE CLASSIFICATION METHOD AND SYSTEM BASED ON DEEP LEARNING, ELEC TRONIC APPARATUS, AND STORAGE MEDIUM =(5 4) IT,:4 T t n i:*3 M fl A H~jL~ F # TLRky#Q4T A it~~ A M R 4 Sib S10 OBTAIN AT LEAST ONE PICTURE SENT BY A Jt} 4 4 4 TERMINAL DEVICE, THE PICTURE HAVING VEHICLE LICENSE PLATE INFORMATION OF A CORRESPONDING - 4 ~J~vrti7 VEHICLE -, 4 S11 PRE-PROCESS THE OBTAINED AT LEAST ONE N # P-A PICTURE, SO THAT THE PRE-PROCESSED AT LEAST ONE PICTURE MATCHES AN INPUT PARAMETER OF A PRE-TRAINED RECOGNITION MODEL S12 INPUT THE PRE-PROCESSED AT LEAST ONE PICTURE INTO THE PRE-TRAINED RECOGNITION ~At 4~I ~nA~4ItMODEL, RECOGNIZE VEHICLE USE INFORMATION AMP * f~ I x V CORRESPONDING TO THE AT LEAST ONE PICTURE BY -fJ 1 4. > , # AT USING THE PRE-TRAINED RECOGNITION MODEL, AND hi, AA, Y7SEND THE VEHICLEUSE INFORMATION 1 51 . A itCORRESPONDING TO THE AT LEAST ONE PICTURE TO THE TERMINAL DEVICE N (57) Abstract: A vehicle license plate classification method and system based on deep learning, an electronic apparatus, and a storage er medium, applied to the electronic apparatus. The method comprises: obtaining at least one picture sent by a terminal device; pre-pro Ocessing the obtained at least one picture, so that the pre-processed at least one picture matches an input parameter of a pre-trained recognition model; and inputting the pre-processed at least one picture into the pre-trained recognition model, recognizing vehicle use r information corresponding to the at least one picture by using the pre-trained recognition model, and sending the vehicle use information corresponding to the at least one picture to the terminal device. The present invention can automatically recognize the vehicle use in the picture accurately, and can perform accurate classification, thereby improving the accuracy and work efficiency. W O 2017/220032 A20032AlII|I||||||I|I|I|||||||||I||I|||||I|I||||||||||||||||||||| SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZWc (84) 1'T(tMtfyd, 3*4-Pi4fftf9 f {ffdt) : ARIPO (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW), K[ R (AM, AZ, BY, KG, KZ, RU, TJ, TM), KUl (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, Fl, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG). fftAtIt tG'Jtt% x~tAM#Ef#72 2Fi4{mg-4tEtRAtx Vl @~Th½5, (57) EW'tM~iFim -Exm*WifA 4FimeR~ioMif ll &##e *I 0 EVII ln irK ff7o n,@V qJii vR $@$ f)" W i N #elenkM rH0f EI 9A*R n,~