Abstract

We present a distortion-tolerant 3-D object recognition system using single exposure on-axis digital holography. In contrast to distortion-tolerant 3-D object recognition employing conventional phase shifting scheme which requires multiple exposures, our proposed method requires only one single digital hologram to be synthesized and used for distortion-tolerant 3-D object recognition. A benefit of the single exposure based on-axis approach is enhanced practicality of digital holography for distortion-tolerant 3-D object recognition in terms of its simplicity and high tolerance to external scene parameters such as moving targets. This paper shows experimentally, that single exposure on-axis digital holography is capable of providing a distortion-tolerant 3-D object recognition capability.

© 2004 Optical Society of America

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References

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Appl. Opt. (6)

Appl. Phy. Lett. (1)

J. W. Goodman, R. W. Lawrence, �??Digital image formation from electronically detected holograms,�?? Appl. Phy. Lett. 11, 77-79 (1967).
[CrossRef]

Image Recognition and Classification (1)

A. Mahalanobis, �??Correlation Pattern Recognition: An Optimum Approach,�?? in Image Recognition and Classification (Marcel Dekker, New-York, 2002).
[CrossRef]

J. Opt. Soc. Am. A (2)

Meas. Sci. Tech. (1)

U. Schnars and W. Juptner, �??Digital recording and numerical reconstruction of holograms,�?? Meas. Sci. Tech. 13, R85-R101 (2002).
[CrossRef]

Opt. Lett. (4)

SPIE (1)

F. Sadjadi, eds., Automatic Target Recognition, Proc. SPIE 5426, Orlando, Florida, April (2004).

Other (2)

J. W. Goodman, Introduction to Fourier Optics (McGraw-Hill, New-York, 1968).

J. Caulfield, Handbook of Optical Holography (Academic, London, 1979).

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Figures (9)

Fig. 1.
Fig. 1.

Experimental setup of the distortion-tolerant 3-D object recognition system based on single exposure on-axis scheme.

Fig. 2.
Fig. 2.

Three-dimensional multiple image sectioning and multi perspectives by digital holography.

Fig. 3.
Fig. 3.

Reconstructed images of the reference true target prior to pre-processing by use of (a) single exposure on-axis digital holography and (b) multiple exposures on-axis phase shifting digital holography.

Fig. 4.
Fig. 4.

(a)–(f): Three reconstructed training images from the synthesized hologram #6 by use of (a)–(c) single exposure on-axis digital holography and (d)–(f) multiple exposures on-axis phase shift digital holography.

Fig. 5.
Fig. 5.

Constructed non-linear composite filters for distortion-tolerant 3-D object recognition by use of (a) single exposure on-axis digital holography and (b) on-axis phase shift digital holography.

Fig. 6.
Fig. 6.

Reconstucted images of some false class objects (images: #10, #13 and #15) by use of (a)–(c) single exposure on-axis digital holography and (d)–(f) on-axis phase shift digital holography.

Fig. 7.
Fig. 7.

(a)–(d): Normalized correlation when input image #8 of the non-training true targets and input image #13 among the false class objects are used as input scenes for (a)–(b) single exposure on-axis digital holography and (c)–(d) on-axis phase shift digital holography.

Fig. 8.
Fig. 8.

Normalized correlation distribution for various input images of true targets (#1~#9) and false class objects (#10~#15) for single exposure on-axis digital holography (□) and on-axis phase shifting digital holography (*).

Fig. 9.
Fig. 9.

Normalized correlation peak values versus longitudinal shift along the z axis for single exposure on-axis digital holography (□) and on-axis phase shifting digital holography (*).

Equations (8)

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H ( x , y , θ ) = O ( x , y ) 2 + R ( x , y ) 2 + exp ( i θ ) O ( x , y ) R * ( x , y ) + exp ( i θ ) O * ( x , y ) R ( x , y )
u i M ( x , y ) = O ( x , y ) R * ( x , y )
= 1 2 { [ H ( x , y , 0 ) O ( x , y ) 2 R ( x , y ) 2 ] + i [ H ( x , y , π 2 ) O ( x , y ) 2 R ( x , y ) 2 ] }
u i s ( x , y ) = O ( x , y ) R * ( x , y ) + O * ( x , y ) R ( x , y )
= H ( x , y , 0 ) R ( x , y ) 2 1 N 2 k = 0 N 1 l = 0 N 1 { H ( k Δ x , l Δ y , 0 ) R ( k Δ x , l Δ y ) 2 }
u 0 ( x ' , y ' ) = exp ( i k d ) i d λ exp [ i k 2 d ( x ' 2 + y ' 2 ) ] × F { u i ( x , y ) exp [ i k 2 d ( x 2 + y 2 ) ] }
v k = [ v [ 1 ] k exp ( j ϕ v [ 1 ] ) v [ 2 ] k exp ( j ϕ v [ 2 ] ) v [ p ] k exp ( j ϕ v [ p ] ) ]
h k = F 1 { S k [ ( S k ) + S k ] 1 c * }

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