Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One is that the imag

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2004 RGB A STUDY OF RGB COLOR INFORMATION AND ITS APPLICATION 03R3237

Abstract This paper concerns with a method of dynamic image cognition. Our image cognition method has two distinguished features. One is that the image is handled as its Eigen (characteristic) pattern and time series frequency characteristic. The other is that the cognition is carried out by solving for the ill-posed linear system of equations comprising the Eigen patterns and time series frequency characteristic as a database. The Eigen pattern consists of histograms in RGB color components of the image. This Eigen pattern of color components yields a numerical data set which is hard to be changed by the differences in spatial position of target as well as resolution of the image. The time series frequency characteristic consists of Fourier power spectra of time changing Eigen patterns. This time series frequency characteristic is a distinct frequency characteristic to each of the objects. The image cognition method proposed in this paper is composed of the Eigen pattern and time series frequency characteristic. As a result, it is revealed that the method proposed in this thesis is one of powerful and effective methods of dynamic image cognition. 1

- 目次 - 2

CCD(Charge Coupled Device) [1] [2] ()1/ 1/ 2 [3][4] 3

RGB m n xy xy mn k RGB R k G k B k (1) image pixeli, j (1) pixel R, G, B i, j k k k i = 1,2,3,.,m j = 1,2,3,., n k = 1,2,3,., m n R G B R IR I R R k (2) k = 1,2,3,., m n R IR D R IR D (3)Round[* ]Max[* ] D Rk I R Round D (3) Max[ I R ] k = 1,2,3,., m n (3) D R IR D 1 D Count[* p] p 4

D E R Count[ I R, p] p = 1,2,3,., D (4) (4) ER R G B E E R G B (5) 255 [3] 1 E = E, E, E ] (5) [ R G B [Mag.] [Mag.] [No.] [No.] [Mag.] [Mag.] [No.] [No.] (a) 1300 300 (b) 2100 100 RGB CCD 29.97 RGB 5

RGB 1 [5] [Mag.] [Mag.] [No.] [No.] 6

() () [Mag.] [Mag.] [No.] [No.] 7

RGB RGB 1/ 1/ / / 1 1/1/ 2 [Power] 1 0.1 0.01 1/f 0.001 0.0001 1/ 2 1 10 100 1000 10000 [Frequency] CCD RGB 8

RGB RGB RGB [Amp.] RGB [Time] DFT DFT DFT 1/4 DFT [Power] [Power] [Power] [Frequency] [Frequency] [Frequency] (a)r (b)g (c)b 1/ RGB n (6) 9

f = y, y y,, y ] (6) [ 1 2, 3 n (7) X i = logi Yi = log yi a n n i= 1 Y i= 1 i i i i= 1 i= 1 i= 1 = n n n n X Y Y i i n X Y n i i= 1 Y Y i i (7) (7) RGB R=0.24 G=0.21 B=0.12 1/ 1 RGB ()1 RGB RGB 1 255 (a)(b) (11) (c) F = E, E,, E ] n: (11) [ 1 2 n [Mag.] [Mag.] [Frame.] [No.] [No.] (a) (b) (c) 10

() DFT 1/4 RGB 1 255 RGB 1 1/ 0 (c) RGB RGB 255 1/ RGB 255 [6] [Inclination] [No.] RGB 1 255 LED 1/ 1/ 0.5 LED 1/ 1/ 1/ 1/ 1/ (12) 1/ 1/ (12) n 1/ 11

filter = 1 1 1 1 1 1 1 1 1 0,1,,,,,,,,, 1 2 3 n n n n n 2 1 1 2 3 2 2 2 2 2 2 (12) [Amp.] [Amp.] [Time] [Time] 1/ 1/ 1/ 1 [Power] [Power] [Frequency] [Frequency] 1/ 1/ DA LED CCD CCD (29.97Hz) 1/ 0.5 1/ LED 1/ 0.5 LED1/ LED 12

1/ 0.5 1/ LED 1/ 0.5 LED 1/ LED LED RGB 1/ 0.5 LED 0.5 1/ LED RGB RGB 1 255 RGB DFT 1 13

RGB 1/ RGB 1/1/ 0.5 1/ 14

2 1 3 CCD 1 n n (13) C = E, E, E,, E ] (13) [ 1 2 3 n Y (14)X (13) (13) Y = C X (14) 765 n C (14) [7] X e (15) 15

e = Y CX (15) e (16) 2 e 2 = e T = Y e = [ Y CX ] T T Y 2Y [ Y CX ] T CX + X T C T (16) CX 2 e X X (17) X T X 2 e = 2Y = Y T C[ C T T C] C + 2X 1 T C T C = 0 (17) X (18) X T 1 T = [ C C] C Y (18) X [Mag.] [No.] C GVSPM[8] 16

1 R,G,B RGB RGB 9 1 No.1 No.2 No.3 No.4 No.5 No.6 No.7 No.8 No.9 No.10 1 No.1 No.2 No.3 No.4 No.5 No.6 No.7 No.8 No.9 No.10 X 17

(No.1) () (No.2) () (No.3) () (No.4) () (No.5) () (No.6) () 18

(No.7) () (No.8) () (No.9) () (No.10) () 1 No.8 19

(No.1) () (No.2) () (No.3) () (No.4) () (No.5) () 20

(No.6) () (No.7) () (No.8) () (No.9) () (No.10) () 1 No.8 21

CCD CCD CCD CCD CCD X CCD (No.11) (No.1) () (No.2) () (No.3) () (No.4) () 22

(No.5) () (No.6) () (No.7) () (No.8) () (No.9) () (No.10) () (No.11) () 3CCD 3 CCD (No.11) 23

() 2 [Mag.] [No.] 1 No.1No.2 No.6 24

No.1 No.2 No.3 No.4 No.5 No.6 No.1 No.2 No.3 No.4 No.5 No.6 25

(No.1) () (No.2) () (No.3) () (No.4) () (No.5) () (No.6) () 26

(No.1) () (No.2) () (No.3) () (No.4) () (No.5) () (No.6) () 27

3CCD (No.1) () (No.2) () (No.3) () (No.4) () (No.5) () (No.6) () 28

(No.7) () (No.8) () (No.9) () (No.10) () (No.11) () (No.12) () 29

(No.13) () (No.14) () (No.15) () (No.16) () 3 CCD 3CCD 16 15 1 30

RGB RGB 3 3 CCD 31

[1] vol.23no.1pp.95-982003 [2] Vol.19No.1pp.91941999 [3] 1/ [4] [5] Vol.22No.1pp.243-2462002 [6] Vol.24No.1pp.223-2262004 [7] G. Strang, Linear Algebra and Its Applications, Academic Press, Inc., 1976. [8] Hisashi Endo, Seiji Hayano, Yoshifuru Saito and Kenzo Miya, Generalized Vector Sampled Pattern Matching Method -Theory and Applications-, Studies in Applied Electromagnetics and Mechanics, Vol.23 Electromagnetic Nondestructive Evaluation (VI) (Eds. F. Kojima), IOS Press, The Netherland, pp.285-292, 2002. [9] 1995 [10] 1/ 1978 32