基于机器视觉的水果尺寸检测误差分析-饶秀勤

19 1 2003 M1j。Marchant J. A.(1988) B j . s) j $“d,“d !i) “) 5, V40 . s),“ds) ? L= 311。 Churchill. D. B(1992)1 j $/ _ 0B M 3 0、 z H ,?C, j $_1 _ , HW9 _ sB2。 Trooien T. P.( 1992 Ma,b,c) j $“d _ . =3 ZE,iy 1 ,TV j $_ =3 L=3 M13。Panigrahi S.(1995) y 0j,4 BVs 0m14/,i 0Kv、Kv zZ_ 5mm BQ z, TM1sY0. 998、 0. 9970. 970, 4。l( 2000)y m$8W 1“$ ,4 8H p8USZE,7 V j$/ _ TjV J ,_r96% 5。?( 2000)G 、 T o+# +,4 Tg B? 9 ,_ (M6. 67% 6 , r(1997)4iy VgmoT LV + + MEHME, (MsY7. 68%8. 01% 7。 D ( 3yTBs。Tj_ Ts)V1B,NV 3y,h _4 j $s) q 1il。kv T%、 T ( o,Ls, o89L= Ts。7 (T (, 9 ,yNs9Bkil。2 SN y /: m1a U, O1i;,O2 T,A1B1S,A1 gA1, TV A(A1B1= AB) gA。图 1 三类误差Fig. 1 Three types of errors121L H,OA19OA, m1a U,ABSA1B1 ,yN 3。m1a,hA W, H; W。 W+ 1“,i:OAOA1= HH - h (1)N7 M:E= hH - h (2)hvl | %A o ,yNMvlA1。MKvo ),N Hh= 2REmax = 2RH - R (3)L= !9;vQ H, T k , V “d1 p# T ( ;H= R(1+ 2E ) (4)E |1% H, H= 201R, Vn, H R。N Vn, T o,V M, P, SM,7 L= 3,|Sb S,A 。 S。3 m1b U,i; T g。 TV |BA, PAOA o A M,;L ?L.l,A T g , L H, T TR。 + 1“,AO1O2:H - R(H - R)2 - R2 =Rr (5)T r AB。e(5) T:R= r 1+ R2(H- R)2 - R2 = r 1+1( HR - 1)2 - 1(6)Vn T L=j Wi, H,;LEV TKv )YV7,。 S;v“d1 p,H R,V:R= r (7)4 m1c U,i;O1 TO2 g, Tj_B f 。YV;O1;L TO2 MsYA、B, gsYA、B,m1c Vn,g1“M, T g BS,i; T g7 3, 。O1,ABY,y m1c U US“,5O1US(0,0, H), oUS(0,e,R),ei; T gW , o , VYV g9 ZE9 。 oO2Zx2+ (y - e)2+ (z - R)2 = R2 (8)YV o B(x0,y0,z0) O o M M :xx0+ yy0+ zz0 - e(y+ y0) - R(z - z0)+ e2 = 0(9)|;O1( 0,0, H) T(7) VYV; O oO2M M o US,tXOY g oO2 。Hz0 - ey0 - R(H - z0)+ e2 = 0 (10)(10):z0 = ey0+ RH - e2H - R (11)A、BXOY USsY( 0,e - r2)、 (0,e+ r1),r2r1 VsYYV 9 ,| B T V9 oR。 |A( 0,e - r2) T, o AZUS:z0 = RH - er2H - R (12)|A( 0,e - r2,z0) o Z T,:e2+ (RH - er2H - R - R)2 = R2 (13) S;v“d1 p, H R, V:R = e 1+ r2H2(14)5 s Tj_S、3y,i 9 Svl T T T。h _4 j $s) q, Ts) 3L 7?4 G ,i V _4k。 I D1 Marchant J A, Onyango C M, Street M J. High speedsorting of potatoes using computer visionJ. ASAE PaperNo. 88- 3540,1988.2 Churchill D B, Bilsland D M, Cooper T M. Comparison ofmachinevision with human measurement of seed dimensionsJ. Transactions of the ASAE, 1992,35(1): 61 64.3 Trooien T P, Heermann D F. Measurement and simulationof potato leaf area using imageprocessing J. Transactionsof the ASAE, 1992a,b, c,35(5): 1709 1712, 1713 1718,122 j2003 M and 1719 1721.4 Panigrahi S, Misra M K, Bern C, et al. Backgroundsegmentation and dimensional measurement of corngermplasm J. Transactions of the ASAE,1995, 38(1): 291 297.5 l, W,u . j $/ j 1 MY( ) J. j, 2000,16(1): 103 108.6 l, W,u . j $/ j 1 MYZJ. j, 2000,16( 3): 4 8.7 l,_.g. j $/ j 31J. j,1999, 15(3): 199 203.8 l. Tj j $_ZEJ.v: j 3 S, 2000,26( 3): 229 232.9 ?,f 4, ;.B T _ J. 2 jv, 2000, 21(2): 85 87.10 r, , .T L J 9 j $J. j, 1997,13(4): 156 160.11 c,l. Tm) #j_J.j, 2001, 13(4): 214 217.12 l,e . T j $ MYZEJ.j, 1999, 15(1): 192 196.13 l,e . j $/ jT J_J. j, 1999,15( 1): 197 200.14 c,l. TTV J9 j $_ZEJ.v: j 3 S, 2001,27(5): 583 586 .15 a f, , y B.9 j $“dm #s J. j, 1995,11( 1): 76 81.16 Y,l. j $/ jT0 _ZJ. j, 2001,017(006): 175179.Analysis of errors in fruit size inspectingbased on machine visionRao Xiuqin, Ying Yibin(Collegeof Bio-system Engineeringand Food Science, Zhejiang University. Hangzhou 310029, China)Abstract: Research advancements on fruit size inspecting with machine vision was introduced. The relationshipamong fruit, camera lens and fruit image was studied based on geometric optic theory. Pixels in the fruit imagestand for varied actual size because of varied positions of points on the fruit surface, which gave rise to calibrationerrors. The distance betweencamera and fruit was limitedand not long enough to obtain the actual radius from theimage, which caused radius errors. Since thelocation of the fruit relates to the core of the camera, the shapeon theimage was varied, which resultedin shape errors. Three formulas were set up t