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A novel secret image A novel secret image sharing scheme for sharing scheme for

true-color images with true-color images with size constraintsize constraintSource: Information Sciences, Vol. 179, Source: Information Sciences, Vol. 179,

No. 19, No. 19, Sep.2009,pp.3247- Sep.2009,pp.3247-3254.3254.

Author: Tsai Du-Shiau, Horng Gwoboa,Author: Tsai Du-Shiau, Horng Gwoboa, Chen Tzung-Her, Huang Yao-TeChen Tzung-Her, Huang Yao-Te

Article history:Article history:Received 2 August 2008Received 2 August 2008Received in revised form 21 May 2009Received in revised form 21 May 2009Accepted 29 May 2009Accepted 29 May 2009

Advisor: Chih-Hung LinSpeaker: 趙家寬

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OutlineOutline

IntroductionIntroduction Review of related worksReview of related works The proposed schemeThe proposed scheme Experimental resultsExperimental results DiscussionDiscussion ConclusionsConclusions

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Introduction(1/3Introduction(1/3)) Secret Image Sharing (SIS)Secret Image Sharing (SIS)

Distributing partial information, Distributing partial information, called sharescalled shares

Two types of SISTwo types of SIS

1.1. LosslessLossless

2.2. Lossy Lossy

FunctionFunction

; and; and

..

)(' ii XfX

)(f

))((1 ii XffX

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Introduction(2/3Introduction(2/3))

Three main categories of SISThree main categories of SIS

1.1.VC-based(VC-based( 視覺密碼學視覺密碼學 ))

2.2.VVSS-based (VVSS-based ( 變異視覺式機密分享變異視覺式機密分享 ))

3.3.IM-based(IM-based( 插值方法插值方法 ))

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Introduction(3/3Introduction(3/3))

Four guidelines to propose a new Four guidelines to propose a new SIS scheme SIS scheme

1.1. Support 24-bit true-color image Support 24-bit true-color image

2.2. Size of each share is slightly increased Size of each share is slightly increased

3.3. Camouflage images for hiding secrets Camouflage images for hiding secrets should be natural should be natural

4.4. Visual perception and image properties Visual perception and image properties

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Review of related Review of related works(1/7)works(1/7)

1.1. VC-based secret image sharing VC-based secret image sharing schemes (Proposed by Naor and schemes (Proposed by Naor and Shamir)Shamir)

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Review of related Review of related works(2/7)works(2/7)

Characteristics Characteristics

1.1. Perfectly secure Perfectly secure

2.2. Decode secrets by visual systems with Decode secrets by visual systems with no cryptography knowledge and without no cryptography knowledge and without performing cryptographic computationperforming cryptographic computation

3.3. Transparencies are meaningless Transparencies are meaningless

4.4. Size of each transparency is much larger Size of each transparency is much larger than that of secret images than that of secret images

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Review of related Review of related works(3/7)works(3/7)

2.2. VVSS-based secret image sharing VVSS-based secret image sharing schemes (Proposed by Chang et al.)schemes (Proposed by Chang et al.)

• Give three n x m pixels image - C-color secret Give three n x m pixels image - C-color secret image S and two image S and two randomly chosen cover images chosen cover images OO11 and O and O22

• Colors of S is stored in the Color Index Table (CIT)Colors of S is stored in the Color Index Table (CIT)

• Each pixel in OEach pixel in O11 and O and O22 is expanded into is expanded into minimizedminimized subpixels to obtain two subpixels to obtain two camouflage images, Ocamouflage images, O11’’ and O and O22’’

ttM

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Review of related Review of related works(4/7)works(4/7)

MM satisfies : satisfies :

(3)(3)

(4) (4)

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Review of related Review of related works(5/7)works(5/7)

Bit-level based SIS schemeBit-level based SIS scheme

(Proposed by Lukac and Plataniotis)(Proposed by Lukac and Plataniotis)

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Review of related Review of related works(6/7)works(6/7)

4.4. PCA and FFN neural networksPCA and FFN neural networks Principal component analysis Principal component analysis

(PCA)(PCA) Color image compression scheme Color image compression scheme

with hybrid neural network with hybrid neural network consisting of Sangerconsisting of Sanger’’s algorithm s algorithm

(Proposed by Clausen and (Proposed by Clausen and Wechsler)Wechsler)

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Review of related Review of related works(7/7)works(7/7)

The neural network begins with initial A The neural network begins with initial A and learns/updates weights aand learns/updates weights aijij according according toto

A feed forward neural network trained with A feed forward neural network trained with back propagation also begins with initial B back propagation also begins with initial B and learns/updates weights bij according toand learns/updates weights bij according to

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The proposed The proposed scheme(1/4)scheme(1/4)

1)1) Initial phaseInitial phaseTwo global weighted matrices A and BTwo global weighted matrices A and B

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The proposed The proposed scheme(2/4)scheme(2/4)

2)2) Encoding phaseEncoding phase• Input: a true-color secret image XInput: a true-color secret image X• Output: n camouflage imagesOutput: n camouflage images

(11)(11)

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The proposed The proposed scheme(3/4)scheme(3/4)

(12)(12)

(13)(13)

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The proposed The proposed scheme(4/4)scheme(4/4)

3.3. Decoding phaseDecoding phase• Input: n camouflage images, global Input: n camouflage images, global

weighted matrix B, seed sweighted matrix B, seed s• Output: true-color secret image XOutput: true-color secret image X’’

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Experimental resultsExperimental results

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Discussion(1/2)Discussion(1/2)

1)1) Support the 24-bit true-color secret imageSupport the 24-bit true-color secret image2)2) Size constraint on sharesSize constraint on shares3)3) Quality improvement Quality improvement

4)4) Efficiency of bandwidth and storage space Efficiency of bandwidth and storage space 5)5) Security enhancement Security enhancement 6)6) Low computational power Low computational power

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Discussion(2/2)Discussion(2/2)