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J.-S. Pan, S.-M. Chen, and N.T. Nguyen (Eds.): ICCCI 2010, Part I, LNAI 6421, pp. 81–89, 2010. © Springer-Verlag Berlin Heidelberg 2010 Optical Image Encryption Based on Joint Fresnel Transform Correlator Hsuan-Ting Chang * and Zong-Yu Wu Photonics and Information Laboratory, Institute of Communications Engineering, National Yunlin University of Science and Technology, Douliu Yunlin, 64002 Taiwan R.O.C. Abstract. Optical verification systems can make image hide in high-security phase key through the phase retrieval operation Conventionally, optical verifi- cation systems based on the joint transform correlator usually use Fourier trans- form. In this paper we propose the joint Fresnel transform architecture and use the methods of the projection onto constraint set and nonlinear transform to de- termine the pure phase key. As shown in our simulation results, the advantages of the proposed method include that our system is lensless and the additional wavelength and distance parameters enhance the system security. Keywords: Image encryption, Fresnel transform, phase retrieval, nonlinear transform. 1 Introduction In current communication systems, cryptography [9-11] is an important issue because the information is easily attacked, stolen, or forgery. Encryption for information is indispensable. The developing of systems and technologies in optic can create more developmental and application. Compared to the previous digital encryption, optical encryption is faster, the computing speed equivalent to the light, and having characte- ristics of parallel processing in image signal. The other, the optical encryption can store in the form of phase and amplitude. In contrast, the optical encryption has a large space for development. The demand on the device, optical system needing more precise of instruments in encrypting and decrypt, so the invasion risk is reduced. Previous joint transform correlators (JTCs) calculate far-field projection by using the optical Fourier transform (FT), then through CCD(Charge-Coupled Device) to receive image intensity, and implement IFT (Inverse Fourier Transform) to get target image. Reference to this framework, we propose FrT (Fresnel Transform) [14] to calculus near-field projection, thus can making lensless and increase distance parame- ters. In the latter segment of this system, we using POCS (Projection Onto Constraint Set) [2], [8], [12], [13] to iterate the reconstruct information to pure phase mask [3~7]. To make all of the operations based on pure phase, we using nonlinear transform and normalize to convert amplitude to phase. We reference to the iterative encrypt system * Corresponding author. [email protected]

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Page 1: Optical Image Encryption Based on Joint Fresnel · PDF fileOptical Image Encryption Based on Joint Fresnel Transform Correlator 87 Fig. 9. Variation of the CC values between the original

J.-S. Pan, S.-M. Chen, and N.T. Nguyen (Eds.): ICCCI 2010, Part I, LNAI 6421, pp. 81–89, 2010. © Springer-Verlag Berlin Heidelberg 2010

Optical Image Encryption Based on Joint Fresnel Transform Correlator

Hsuan-Ting Chang* and Zong-Yu Wu

Photonics and Information Laboratory, Institute of Communications Engineering, National Yunlin University of Science and Technology,

Douliu Yunlin, 64002 Taiwan R.O.C.

Abstract. Optical verification systems can make image hide in high-security phase key through the phase retrieval operation Conventionally, optical verifi-cation systems based on the joint transform correlator usually use Fourier trans-form. In this paper we propose the joint Fresnel transform architecture and use the methods of the projection onto constraint set and nonlinear transform to de-termine the pure phase key. As shown in our simulation results, the advantages of the proposed method include that our system is lensless and the additional wavelength and distance parameters enhance the system security.

Keywords: Image encryption, Fresnel transform, phase retrieval, nonlinear transform.

1 Introduction

In current communication systems, cryptography [9-11] is an important issue because the information is easily attacked, stolen, or forgery. Encryption for information is indispensable. The developing of systems and technologies in optic can create more developmental and application. Compared to the previous digital encryption, optical encryption is faster, the computing speed equivalent to the light, and having characte-ristics of parallel processing in image signal. The other, the optical encryption can store in the form of phase and amplitude. In contrast, the optical encryption has a large space for development. The demand on the device, optical system needing more precise of instruments in encrypting and decrypt, so the invasion risk is reduced.

Previous joint transform correlators (JTCs) calculate far-field projection by using the optical Fourier transform (FT), then through CCD(Charge-Coupled Device) to receive image intensity, and implement IFT (Inverse Fourier Transform) to get target image. Reference to this framework, we propose FrT (Fresnel Transform) [14] to calculus near-field projection, thus can making lensless and increase distance parame-ters. In the latter segment of this system, we using POCS (Projection Onto Constraint Set) [2], [8], [12], [13] to iterate the reconstruct information to pure phase mask [3~7]. To make all of the operations based on pure phase, we using nonlinear transform and normalize to convert amplitude to phase. We reference to the iterative encrypt system * Corresponding author. [email protected]

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82 H.-T. Chang and Z.-Y. Wu

for one image and one random phase mask based on FrT, and two types of nonlinear conversion. According to the idea of using near-field projection and the algorithm of pure phase mask, we proposed the joint Fresnel transform system as shown in Fig. 1.

Section 2 is divided into optical iterative encryption and nonlinear transform, we will introduce the calculus process of POCS algorithm for enhance the quality of reconstruction, and the use of nonlinear transformation. The experiment of Section 3, we using image example to test this algorithm by MATLAB, and using the results of MSE (Mean square error) and CC (Correlation coefficient) to verify the quality of this algorithm. The final section, we referred to conclusions of this algorithm and the development of future applications.

Fig. 1. The proposed joint Fresnel transform system for optical image encryption

2 Encryption algorithm

2.1 POCS

The flow chart of our system divided into the iteration part (red block) and the transform part (green block), which are shown in Fig. 2. In conversion operation of signals, we use the near-field projection for FrT. FrT{Η (x,y);z} = h , , where k .

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Optical Image Encryption Based on Joint Fresnel Transform Correlator 83

In the iteration part, we give an original image g and it is transformed with the FrT, the transform distance is z2 (the block diagram is shown in Fig. 3), such as Eq. (1):

t(x2,y2)exp[js(x2,y2)] = IFrT{g(x3,y3);z2} (1)

t is the part of amplitude and s is the part of phase. We extract s to convert by FrT, such as Eq. (2):

g’(x3,y3)exp[ jψ(x3,y3)] = FrT{exp[ js(x2,y2)];z2} (2)

We make the amplitude g’ to normalize, judge with g for pixel error. If some pixel error is greater than threshold that we enter, the pixel of g’ can replace by the same position pixel of g. After the judge, we using the new image to multiplied by , and

continue to execute the next loop by back to Eq. (1), and so on.

Fig. 2. The systematic block diagram of the proposed joint Fresnel transform system

2.2 Nonlinear Transform

In the nonlinear transform operation, we use to two common schemes: (1) Power-law transform:

(2) Log-sigmoid transform:

In convert part, we using the random phase key h to convert by FrT is shown in Eq. (3):

H(x2,y2) exp[ jψH(x2,y2)] = FrT{exp[ jh(x1,y1)];z1} (3)

ψ

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84 H.-T. Chang and Z.-Y. Wu

Then we use the part of amplitude H to calculate the signal intensity O, which is shown in Eq. (4):

O(x2, y2) = | H(x2,y2) |2 (4)

Then we normalize O to [0, 1] to obtain O’. Finally, let O’ convert to Ψ by using the nonlinear transform and normalize Ψ to [-π, π]. Then we store the result to P.

2.3 Combination Calculation

After the previous of pure phase s and the target image g’, in order to combine the results, we divided s to P to obtain the phase mask φ is shown in Eq. (5):

(5)

After the phase ϕ is obtained, that can make our operation s to achieve a coherent. Entering a Correct phase key get through calculus will obtain the target image g’ in this system, we get keys of distance parameters z1, z2 and the modulation parameters used in the nonlinear transform.

Fig. 3. Optical Fresnel transform between two planes

3 Simulation Results

The computer simulation is done by using MATLAB. The size of target image is 256 × 256, such as Fig. 4(a). The distance of FrT, z2 = 20cm, wavelength λ = 632.8 nm. The iteration number is set to 100, the threshold value of MSE is set as five.

After the above calculation obtain phase mask s and approximated image g’ is shown in Fig. 4(b) and 4(c), respectively. The CC values between g’ and g is 0.9928. We use a random phase to be the input phase key, such as Fig. 5(a). Set the convert distance z1 to 12 cm and the wavelength λ to 632.8 nm for FrT. After the signal intensity is obtained,

)],(exp[)],(exp[

= )],(exp[22

2222 yxPj

yxsjyxjφ

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Optical Image Encryption Based on Joint Fresnel Transform Correlator 85

(a) (b) (c)

Fig. 4. (a) The target Len image; (b) the reconstructed image g’; (c) Phase key s

we use the Log-sigmoid transform as the nonlinear transformation, in which the para-meters are a = -5,c = 10. After the processing of signal conversion, the pure phase P can be obtained, such as that shown in Fig. 5(b). Then following Eq. (5), we can obtain the other phase φ, which is shown in Fig. 5(c). After an overall operation, the obtained image is shown in Fig. 5(d) which is similar to that in Fig. 4(b).

Consider the sensitivity of different system parameters. Following the previous set-ting, if we enter the distance parameter z1 = 19 cm, and 15 cm, the reconstructed im-ages are shown in Figs. 6(a) and 6(b), respectively. Figure 7 shows the variation of

(a) (b) (c) (d)

Fig. 5. (a) The random phase key; (b) Phase key P; (c) Phase key ϕ; (d) The verified image g’

(a) (b)

Fig. 6. The reconstructed images under incorrect distance parameters; (a) z1 = 13cm; (b) z1 = 17cm

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86 H.-T. Chang and Z.-Y. Wu

CC values between the original image and reconstructed image for z1 in the range from 1cm to 50 cm (Take a sample of each cm). If we enter the distance parameter z2 =

19 cm and 15 cm, the reconstructed images are shown in Figs. 8(a) and 8(b), respec-tively. We plot the variation of the CC values between the original image and recon-structed image for the z2 parameter from 1 cm to 50 cm (Take a sample in each cm), which is shown in Fig. 9.

Fig. 7. Variation of the CC values between original image and reconstructed image for the z1 parameter

(a) (b)

Fig. 8. The reconstructed images for the incorrect distance parameters: (a) z2 = 19cm; (b) z2 = 15cm

Considering the wavelength λ = 682.8nm, the reconstructed image is shown in Fig. 10(a). When the wavelength λ = 832.8nm, the reconstructed image is shown in Fig. 10(b). We plot the variation of the CC values between the original image and reconstructed image for the wavelength λ ranging from 332.8 nm to 832.8 nm (Take a sample in each 10nm), which is shown in Fig.11.

0 10 20 30 40 500

0.1

0.2

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Optical Image Encryption Based on Joint Fresnel Transform Correlator 87

Fig. 9. Variation of the CC values between the original image and reconstructed image for the z2 parameter

(a) (b)

Fig. 10. The reconstructed images of two wavelengths: (a) λ = 682.8nm; (b) λ = 832.8nm

Fig. 11. Variation of the CC values between the original image and reconstructed image for the λ parameter

0 5 10 15 20 25 30 35 40 45 50

-0.2

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350 400 450 500 550 600 650 700 750 800-0.1

0

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88 H.-T. Chang and Z.-Y. Wu

However, we found that the parameter can’t use for all real numbers in the nonli-near transform. Inappropriate parameters will make the system wrong and operational failure, finally decrease the safety. Trough the computer simulation, we try to found the appropriate interval of parameters. We use the incorrect phase key to replace the phase key h1 to test for Log-sigmoid transform. In processing of parameters, if a = 0, converted values will make no effects in system. We plot the varies of MSE and CC between original image and reconstructed image for a in -10 to 10 and c in -10 to 10, which are shown in Figs. 12 and 13, respectively.

Fig. 12. Variation of the MSE values between original image and reconstructed image under the various nonlinear parameters a and c

Fig. 13. Variation of the CC values between the original image and reconstructed image under the various nonlinear parameters a and c

4 Conclusion

In this paper, we proposed an optical encrypt system based on the joint Fresnel trans-form. The frequency part of an image is converted to a pure phase mask. Then, with

-10-5

05

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Optical Image Encryption Based on Joint Fresnel Transform Correlator 89

the nonlinear transform methods, the target can be reconstructed by using two phase keys in the overall optical system. The proposed structure is simpler than that in con-ventional joint transform correlator architecture because of using no lenses in the proposed system. Moreover, the wavelength and the distances between two phases are two additional encryption parameters which can further enhance the system security level. The quality of system is estimated using the values of MSE and CC between the decrypted and original images.

Acknowledgment

This work is partially supported by National Science Council, Taiwan under the con-tract number NSC 99-2221-E-224-004.

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