arXiv:1502.07993v1 [cs.CR] 26 Feb 2015 · 2018. 4. 25. · Cheque Truncation System(CTS) is an...

Secret Image Sharing Based Cheque Truncation System withCheating Detection

Sreela.S.Ra, G. Santhosh Kumarb, Binu.V.Pc

aDepartment of Computer Science, Cochin University of Science and Technology

bDepartment of Computer Science, Cochin University of Science and Technology

cDepartment of Computer Applications, Cochin University of Science and Technology

Cheque Truncation System(CTS) is an automatic cheque clearance system implemented by RBI.CTS usescheque image, instead of the physical cheque itself, for cheque clearance thus reducing the turn around timedrastically. This approach holds back the physical movement of cheque from presenting bank to the draweebank. In CTS, digital image of the cheque is protected using standard public key and symmetric key encryptionslike RSA, triple DES etc. This involves a lot of computation overhead and key management. The securityalso depends on the hard mathematical problem and is only computationally secure.Information theoreticallysecure, secret image sharing techniques can be used in the CTS for the secure and efficient processing of chequeimage .In this paper, we propose two simple and efficient secret image sharing schemes and a Cheque TruncationSystem based on these algorithms . In the proposed scheme,the presenting bank is acting as the dealer andthe participants are the customer, and the drawee bank.The dealer should generate the shares of cheque anddistributes it to customer and drawee bank.The validity of the shares are important during the reconstructionprocess. The proposed scheme also suggests a method for cheating detection which identify any invalid sharessubmitted by the customers, using the hashing technique. The experimental results shows that the proposedscheme is efficient and secure compared with the existing scheme.

Keywords : Cheque Truncation System,Secret image sharing,PKI,Pixel expansion,Visual cryptography.

1. INTRODUCTION

Cheques represent a significant segment of pay-ment instruments in India. Cheque TruncationSystem (CTS) or ICS(Image Based Clearing Sys-tem) in India is a project undertaken by Re-serve Bank of India ( RBI) for faster clearing ofcheques. CTS is basically an online image-basedcheque clearing system where cheque images andMagnetic Ink Character Recognition (MICR)data are captured at the collecting bank branchand transmitted electronically.Manual clearing ofcheque needs human intervention and is a timeconsuming task.Cheque truncation [7] involvesstopping the flow of the physical cheques issuedby a drawer to the drawee branch. An elec-tronic image of the cheque is sent to the draweebranch along with the relevant information likethe MICR fields, date of presentation, presenting

banks etc. The point of truncation is left to thediscretion of the presenting bank. Thus Chequetruncation, would eliminate the need to move thephysical instruments across branches and henceresult in effective reduction in the time requiredfor payment of cheques, the associated cost oftransit and delays in processing, etc. This willspeed up the process of collection or realizationof cheques and thus reduce the turn around time.

The system offers following benefits to thebank and customers. Banks can expect mul-tiple benefits through the implementation ofCTS, like faster clearing cycle,better reconcili-ation/verification process. Besides, it reducesoperational risk by securing the transmissionroute.Reduction of manual tasks leads to reduc-tion of errors. Customer satisfaction will be en-hanced, due to the reduced turn around time(TAT). Real-time tracking and visibility of the

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cheques, less fraudulent cases with secured trans-fer of images to the RBI are other possible bene-fits that banks may derive from this solution [8].For Customers CTS / ICS substantially reducesthe time taken to clear the cheques as well in-creases operational efficiency by cutting down onoverheads involved in the physical cheque clearingprocess. In addition, it also offers better reconcil-iation and fraud prevention.The use of the Public Key Infrastructure (PKI)ensures data authenticity, integrity and non-repudiation, adding strength to the entire system.The presenting bank is required to affix digitalsignature on the images and data from the pointof truncation itself. The image and data are se-cured using the PKI through out the entire cy-cle covering capture system,the presenting bank,the clearing house and the drawee bank.This sys-tem needs a lot of computation and overhead inkey management is high.In this paper a secretimage sharing [3] based scheme is proposed.Twoefficient schemes are proposed which are compu-tationally secure and avoids the overhead in keymanagement.A cheating detection scheme is alsoproposed which avoids the use of invalid sharesduring the reconstruction.In the rest of the paper, section 2 describes theCTS Architecture. Section 3 describes the re-lated work.Proposed system and algorithms areexplained in section 4. Experimental results arediscussed in section 5 and the conclusions aredrawn in section 6.

2. CTS ARCHITECTURE

The process flow of CTS is explained below. InCTS, the presenting bank (or its branch) capturesthe data on the MICR band and the images ofa cheque using their Capture System comprisingof a scanner, core banking or other application.Images and data should meet the specificationsand standards prescribed for data and images.The architecture of CTS is explained in figure 1.

To ensure security, end-to-end Public Key In-frastructure (PKI) has been implemented in CTSfor protecting data and image. The presentingbank sends the data and captured images dulysigned and encrypted to the Clearing House (the

Figure 1. CTS Architecture

central processing location) for onward transmis-sion to the paying bank (destination or draweebank). For the purpose of participation the pre-senting and drawee banks are provided with aninterface / gateway called the Clearing HouseInterface (CHI) that enables them to connectand transmit data and images in a secure andsafe manner to the Clearing House (CH). TheCTS uses public key infrastructure(PKI) likedigital signature and encryption for protectingcheque images and data. The standards definedfor PKI are hash algorithm SHA-1, padding al-gorithm,RSA asymmetric encryption with 1024bit key length, Triple DES (3DES, TDES) sym-metric encryption with 168 bit key length, andCertificates in x.509v3 format.Cheque image isprotected using encryption techniques. Thesetechniques need a lot of computation and usageof keys.

3. RELATED WORK

CTS system is implemented by RBI to re-duce the complexity of cheque processing. CTSsystem is implemented in India in 2010. Gridbased CTS is implemented in Chennai, Delhi,Kolkata etc. The different security schemes areapplied in cheque.Pasupathinathan, Vijayakrish-nan, Josef Pieprzyk, and Huaxiong Wang [15] de-

Secret Image Sharing Based CTS with Cheating Detection 3

scribes privacy enhanced electonic cheque systemin 2005. In 2011, Rigel Gjomemo,Ha.z.Malik,Nilesh Sumb,V.N. Venkatakrishnan and RashidAnsari [14] explains the digital cheque Forgeryattack on CTS. Kota, Saranya, and RajarshiPal[16] explains the method for detecting tam-pered cheque images in CTS Using Difference Ex-pansion Based Watermarking in 2014.The secret image sharing schemes are based onvisual cryptography, number theory [6], infor-mation hiding theory, error diffusion technique,boolean operation etc. In Yan, Xuehu scheme[10], secret image sharing is based on informationhiding theory. The important technique used inthis scheme are MLE and LSBM. But this schemeis applicable only to the binary images. Chenand Chang [2] use quadratic residue techniquefor secret image sharing. They proposed a (2,2) scheme which is lossy and the lossless schemehaving the share size larger than the secret. Thecomputations involved is also more. Chen, Wei-Kuei, and Hao-Kuan Tso [4] introduced a se-cret image sharing scheme for protecting medi-cal images using Hill cipher method. Thein-LinsScheme enhanced Shamir’s secret sharing scheme[9](Lagrange interpolating polynomial) for pro-tecting digital images.Table1 explains a comparative study on differentsecret image sharing schemes.

4. PROPOSED SYSTEM

The system architecture describes how secretimage sharing scheme happening in the CTS. Inthis architecture, the dealer should be the pre-senting bank. The participants are customer,clearing house (CH), and drawee bank. Figure2 explains the system architecture.In order to reduce the computation and usageof keys, cheque image can be protected using se-cret image sharing. In this paper, two secret im-age sharing methods are proposed for protectingcheque images.If any one of the participants domalpractice on the shares, then cheating occurs.Cheating detection is implemented in this paper.In secret image sharing technique, a secret imageis distributed to some of the participants throughsplitting the image into different pieces called

shares and recover the secret image by collectingthe sufficient number of shares from authorizedparticipants. This field of cryptography is calledvisual cryptography or visual secret sharing [5].If any one of the participant do malpractice ontheir shares, cheating detection methods can beused. It consists of three phases: share genera-tion phase, distribution phase and reconstructionphase.In the share generation phase, the digitalimage is split into different pieces called shares. Inthe distribution phase, the shares are distributedto authorized participants and in the last phase,the image is reconstructed using sufficient numberof shares from authorized participants.In a secretimage sharing scheme, there is a secret image S tobe shared among a set of participants. The secretis known to a special person called dealer. Thedealer generates and distributes partial informa-tion called shares to the participants.(2,3) scheme is required for implementing secu-rity in CTS. Presenting bank generates the sharesand distributed to the clearing house, draweebank and to the customer. Customer should usethe share to get the information of processing ofcheque through online. Drawee bank should re-construct the cheque image using the share fromthe CH and its own share. Drawee bank cant re-construct the cheque image using its own share.To implement security in CTS, xor scheme andpartition scheme can be used.

The important steps involved in the proposedCTS using secret image sharing are as follows:

1. Customer submits the cheque to the pre-senting bank.

2. Capture image of cheque and data usingcapture system

3. Send the data and image to the presentingCHI.

4. Presenting CHI provide security to thecheque image using (3,2) secret image shar-ing scheme.

5. Send first share of the cheque image(SC1)and data to the clearing house through theCHI.


Figure 2. System Architecture

6. Send second share of the cheque image(SC2) to the customer if customer submitscheque through online and this share is usedfor authentication for viewing the details ofcheque processing.

7. The clearing House send data and one shareof the cheque image(SC1) to the draweebank through receiving CHI.

8. The drawee bank request another share ofthe cheque image from the presenting bankthrough receiving CHI.

9. The presenting bank submit third share(SC3) to the drawee bank.

10. The receiving CHI reconstructs the chequeimage using shares SC1 and SC3.

11. Send data to the drawee bank for processingcheque.

12. Bank process the cheque using image pro-cessing algorithm.

In figure 3, the numbers represent the abovesteps.

4.1. XOR schemeXOR scheme is a (2,3) scheme. In this scheme,

three shares are created and the original image is

Figure 3. System Architecture

reconstructed using at least two shares. The im-age is not reconstructed using only one share.Theshare images are created by dividing pixel intofour bits.In this scheme, the share image pixel is4 bits. Share generation algorithm is explainedin Algorithm 1. Recovery algorithm is explainedin Algorithm 2.The original secret image is recon-stucted by using any of the two shares from threeshares.Consider an image matrix is

157 160 190 13089 255 224 19210 220 255 22464 128 192 255

Consider the secret image pixel is 190. Its bi-nary representation is 10111110. The share1pixel(sc1=6(0110)) is created using even bits.Theshare2 pixel(sc2=15 (1111)) is created using oddbits. The share3 pixel(sc3=9(1001)) is createdby xor of s1 s2. The xor scheme is applied on theabove image S. The three shares obtained SC1,SC2 and SC3 are as follows:SC1=

7 0 6 013 15 8 80 14 15 88 0 8 15


SC2= 10 12 15 92 15 12 83 10 15 120 8 8 15

SC3=

13 12 9 915 0 4 03 4 0 48 8 0 0

In this scheme, the size of the share is half of the

Algorithm 1: Algorithm: Share generation1 Input: M X N Secret grayscale image S2 Output: Share images SC1, SC2, SC33 begin

1. For each pixel (i, j)ε{(i, j)|1 ≤ i ≤M, 1 ≤ j ≤ N}repeat steps 2- 4

2. Pixelvalue, pv= S(i,j) which is the binary arraycontaining the pixel intensity binary representation.

3. Create share1 SC1(i, j) pixel using even bits of S(i,j)pixel

SC1(i, j) =

3∑k=0

(pv(2k)× 2k)

4. Create share2 SC2(i,j) pixel using odd bits of S(i,j)pixel

SC2(i, j) =3∑k=0

(pv(2k + 1)× 2k)

5. Create share3 SC3(i,j) pixel by xor ing SC1(i, j) andSC2(i, j)

SC3(i, j, k) = SC1(i, j)⊕ SC2(i, j)

6. Output shares SC1, SC2, and SC3.

end

size of the original image. The number of bits forrepresenting a pixel in share is 4 bits.If the M×Nsecret gray scale image has a size of 8 ×M × Nbits, then the size of the share is only 4×M ×Nbits. So the storage space of the share is reduced.

Algorithm 2: Recovery algorithm1 Input: Share images SC1, SC2, SC32 Output: Reconstructed Secret image S3 begin4 The secret image can be reconstructed from shadow

images SC1, SC2

1. For each position,(i, j)ε{(i, j)|1 ≤ i ≤M, 1 ≤ j ≤ N} repeat step2.

2. S( i , j) is obtained by intermixing bits of SC1(i, j)and SC2(i, j) in even and odd positions respectively.

3. Output image S.

The secret image can be reconstructed from shadowimages SC1, and SC3

1. For each position,(i, j)ε{(i, j)|1 ≤ i ≤M, 1 ≤ j ≤ N}repeat step 2-3.

2. b = SC1(i, j)⊕ SC3(i, j)

3. S(i, j) is obtained by intermixing bits of SC1(i,j) andb in even and odd positions respectively.

4. Output image S.

The secret image can be reconstructed from shadowimages SC2, and SC3.

1. For each position,(i, j)ε{(i, j)|1 ≤ i ≤M, 1 ≤ j ≤ N} repeat step 2-3

2. b = SC2(i, j)⊕ SC3(i, j)

3. S(i, j) is obtained by intermixing bits of b andSC2(i,j) in even and odd positions respectively.

4. Output image S.

end


The quality of the reconstructed image is sameas the original image. In this scheme, there is nopixel expansion on reconstructed image. It is alossless scheme.

4.2. Partition Scheme

Algorithm 3: Algorithm: Share generation1 Input: M X N Secret grayscale image S2 Output: Share images SC1, SC2, SC33 begin

1. Let s be the pixel of the secret image(S) and r be arandom number in 0-255.

2. s is divided into s1 and s2 and r into r1 and r2.

3. Share1 pixel is created by combining s2⊕ r2 and r1

4. Share2 pixel is created by combining s1⊕ r1 and r2

5. Share3 pixel is created by combining s2⊕ r1 ands1⊕ r2

6. repeat step 1-5 until all pixels of image are processed.

7. Output three shares share1(SC1), share2 (SC2),share3(SC3).

Partition scheme is a (2,3) scheme.It usesboolean xor operations. This method uses ran-dom number for creating shares. The share gen-eration algorithm is explained in Algorithm 3 .Algorithms 4, 5, 6 describe the reconstruction ofimage.

4.3. Cheating detection scheme using Hashfunction

A threshold scheme for secret sharing can pro-tect a secret with high reliability and flexibil-ity.These advantages can be achieved only whenall the participants are honest, i.e. all the par-ticipants willing to pool their shadows shall al-ways present the true ones. Cheating detec-tion is an important issue in the secret sharingscheme. However, cheater identification is moreeffective than cheating detection in realistic ap-plications. If some dishonest participants exist,the other honest participants will obtain a falsesecret, while the cheaters may individually obtainthe true one.By applying a one-way hashing func-

Algorithm 4: Algorithm: Reconstruction us-ing share1 and share2

1 Input: Share images SC1, SC22 Output: Reconstructed Secret image S3 begin4 Original image is reconstructed from share1 and share2

by applying following steps.

1. The share1(sc1) pixel is divided into two equal partssc11 and sc12.

2. The share2(sc2) pixel is divided into two equal partssc21 and sc22.

3. The second part of the original image pixel (s2) isreconstructed by XOR-ing first part of the share1pixel(sc11) and second part of the share2 pixel(sc22).

s2 = sc11⊕ sc22

4. The first part of the original image pixel(s1) isreconstructed by XOR-ing second part of the theshare1 pixel(sc12) and first part of the share2pixel(sc21).

s1 = sc12⊕ sc21

5. The original image pixel(s) is obtained by combinings1 and s2.

s = s1.s2

6. repeat the above steps until all pixels are processed.

7. Output image S

end





1. The share1 pixel is divided into two equal parts sc11and sc12.


3. The second part of the original image pixel(s2) isobtained by XOR-ing second part of the share1pixel(sc12) and first part of the share3 pixel(sc31).

s2 = sc12⊕ sc31

4. b = s1⊕ s2 is obtained by XOR-ing first part of theshare1 pixel(sc11) and second part of the share3pixel(sc32).

b = sc11⊕ sc32

5. The first part of the original image pixel(s1) isobtained by s1 = b⊕ s2

6. Secret image pixel(s) is reconstructed by combinings1 and s2

s = s1.s2

7. Repeat above steps until all pixels are processed.

8. Output image S

end






3. The first part of the original image pixel(s1) isobtained by XOR-ing second part of the share2pixel(sc22) and second part of the share3 pixel(sc32).

s1 = sc22⊕ sc32

4. b = s1⊕ s2 is obtained by XOR-ing first part of theshare2 pixel(sc21) and first part of the share3pixel(sc31).

b = sc21⊕ sc31

5. The second part of the original image is obtained bys2 = b⊕ s1

6. Secret image pixel(s) is reconstructed by combinings1 and s2.

s = s1.s2

7. Repeat above steps until all pixels are processed.

8. Output image S

end


tion along with the use of arithmetic coding, theproposed method can be used to deterministicallydetect cheating and identify the cheaters, no mat-ter how many cheaters are involved in the secretreconstruction.Two important theorems used in cheating detec-tion using hash function are as follows. Let ai bethe random shares of the secret data and p be therandomly generated prime number.Theorem 1 [22]: Let T =

∑ni=1 aip

i−1, where0 ≤ ai < p. Then

b T

pj−1c(mod p) = aj (1)

Extended from Theorem 1, we have the followingresult.Theorem 2 [22]: Let T =

∑ni=1 aip

2(i−1)) +∑n−1i=1 cp2i−1, where −p < ai < p and 1 ≤ c < p.

Then

b T

p2(j−1)c(mod p) = aj(mod p) (2)

Combining this result with secret image sharingscheme, the following method is used for cheatingdetection and cheater identification.Algorithm forcheating detection and cheater identification isexplained in Algorithm 7.

The hash value of the image is generated usingcontent of the image. The hash value of theimage is also generated using feature vector ofthe image.In the secret image sharing, any simplechange in the shares is treated as a cheating. Anymild change in the image is reflected in the hashvalue of image using content of image rather thanusing feature vector of image.So we use the hashgeneration method using content of the image.

4.4. Cheque processingCheque processing is implemented in Drawee

bank. In our work, the courtesy amount regionand account number field is recognized.The im-portant steps associated with cheque processingare as follows:

1. Load cheque in grayscale.

2. Find courtesy amount region in cheque us-ing cheque template method .

Algorithm 7: Cheating detection andcheater identification using hash function

1 Dealer generates the shares for cheque image usingsecret image sharing algorithm.

2 He generates public parameters T and p in the followingsteps.

3 Choose a one-way function h(.) and a prime number psuch that h(.) < p. Generates hash value of image usinghash function.

4 Compute T =∑ni=1 h(si)p

(2(i−1)) +∑n−1i=1 cp2i−1 where

c is a positive constant randomly chosen over GF (p)5 Publish T and p.6 Dealer distributes shadow SCi to participants Ui . fori = 1, 2, ..., n.

7 In the receiver side, cheating detection and cheateridentification can easily be achieved by applying thefollowing procedure.

8 Participants UjεG present their possessed shadows SC′jand compute T ′ =

∑UjεG

h(SC′j)p(2(i−1))

9 For each UjεG, check b T−T ′

p(2(j−1))c(mod p)

?= 0

10 If the equation holds, participantUj is honest; otherwise,Uj is a cheater.

3. Find account number region in cheque usingcheque template method.

4. Segment digits in courtesy amount and re-size each digit having a size of 28× 28.

5. Apply digit recognition method for recog-nizing digit in courtesy amount.

6. Combine each digit and generate courtesyamount.

7. Segment digits in account region and resizeeach digit having a size of 28× 28.

8. Apply digit recognition method for recog-nizing digit in account number.

9. Combine each digit and generate accountnumber.

10. Process the amount from the account anddeduct the amount from the account.

11. Send the information to the presenting bankthrough clearing house.

12. At last customer gets the amount from thepresenting bank.


4.4.1. Digit recognizerIn our work, digit recognition is done using

K Nearest neighbour classification technique [28].The isolated components after segmentation arefed into a digit recognizer.The accuracy in rec-ognizing constituent digits plays a big role inthe recognition accuracy of the handwritten cour-tesy amount numeral string. After successful seg-mentation of individual digits from the numeralstring, they have to be correctly recognized toget the value of the cheque.In this, there is twosteps: training phase and testing phase.In train-ing phase, hand written images are trained. Inthe testing phase,the following steps need to becarried out.

• The digit in the image is centered.

• Convert two dimensional array to one di-mensional array using reshape operation.

• Apply the one dimensional array to theKNN classifier.

• The digit is recognized as output.

5. EXPERIMENTAL RESULTS

The algorithms are implemented in Java. Theexperimental result obtained for partition schemeusing the 500 × 225 gray scale cheque image isshown in figure4. The reconstructed image hasthe same quality as original image.This algorithmis also useful for color images.If this algorithmis applied in color images, the algorithm is ap-plied on each channel (Red, Blue, Green) sepa-rately.The bit depth of the share of color image is12 bits.So this scheme is enhanced for color im-ages also. The comparison of above schemes aredescribed in table2.

(a) Secret image

(b) Share1 (c) Share2 (d) Share3

(e) Reconstructedimage

Figure 4. Result of partition scheme

Table 1Comparison of different schemes

Scheme (k,n)threshold

RecoveringMeasure

Loss-less

PixelExpansion

size ofshare

VCS [5] (k,n) Stacking No Yes IncreasesExtendedVCS[11]

(k,n) Stacking No Yes Increases

(k, n2) [10] (k, n2) Mod andBoolean /addition andcomparison

Yes No sameasoriginalimage

(2,3) [6] (2,3) ModandMultiplication

Yes No sameasoriginalimage

Thein-Lin

[12] (r , n) ShamirsSSS(LagrangeInterpolatingpolynomial)

No No Reducesbyhalf

BooleanVSS

[13] (r , n) Booleanoperations

Yes No Increases


Table 2Property comparison of proposed schemes

Scheme RecoveringMeasure

Loss-less

PixelExpansion

size ofshare

xor Boolean Yes No half oftheimagesize

Partition Boolean Yes No sameaschequeimage

The mean square error(MSE) is used to mea-sure the mean square error between original(I)and recovered image(I’) and is calculated by us-ing the equation

MSE =1

MN

∑i=1,M

∑j=1,N

(I ′(i, j)− I(i, j))2

The MSE between original and recovered imageis 0.

In the cheating detection phase, the hash valueof the share images are calculated in the senderside. The value of T is 4.59080713E8. In the re-ceiver side, the hash value is not computed. Thevalue of T’ is computed in the receiver side. If theremainder is zero, the cheating does not occur inthe shares of the cheque image. If the cheatingdoes not occur in the shares, the cheque imageis reconstructed from the shares.Otherwise, thedrawee bank request for the correct shares fromthe participants.In Cheque processing, the courtesy amount andaccount number region are recognised using im-age processing technique.The courtesy amount re-gion in cheque image is shown in fig. 5

The account number region in cheque image isshown in fig. 6 Each digit in courtesy amount andaccount number are segmented and applied to thedigit recognizer. For digit recognition using KNN,the standard dataset MNIST handwritten digitimage is used as training set. MNIST dataset con-tains 60000 image for training purpose. The KNNclassifier give correct result for MNIST testing

Figure 5. Courtesy amount

Figure 6. Account number

images. Some misclassification occured for cour-tesy amount recognition. The courtesy amountrecognised in fig. 5 is 125795.75. The accountnumber reconised in fig. 6 is 12781151507.Theaccount number and amount is fed to the corebanking software and do the transaction opera-tions in software. Drawee bank returns the trans-action details or error message to the presentingbank through Clearing House.

6. CONCLUSIONS

Cheque Truncation system accelerates the pro-cess of collection of cheques resulting in bet-ter service to customers, reduces the scope forclearing-related frauds or loss of instruments intransit, lowers the cost of collection of cheques,and removes reconciliation-related and logistics-related problems, thus benefit the system as awhole.In this paper, two secret image sharingschemes are proposed for provid- ing securityto the cheque image in the CTS. The proposedXOR scheme is simple and effecient but it is notideal.It can be used in low storage device wherememory is a contsraint.The share size is only halfof the original image and it is a lossless scheme.Partition scheme have the properties such as nopixel expansion and lossless scheme. The schemeis also ideal.


The experimental result shows that the pro-posed system provides better security and effi-ciency in Cheque Truncation System.The opera-tions invloved are simple XOR and it also avoidsthe complicated encryption decryption operationswhich are time consuming.The secret image shar-ing scheme doesn’t need any key management andauthentication of the shares are done with simplehash function.The shares are also verified withthe help of public parameters.We are looking for-ward for improved cheque processing using ad-vanced image processing technique which helpsin automatic cheque processing.The operationaleffeciency, speed accuracy, security and authenti-cation are the major design objectives.

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S R Sreela is a ResearchScholar in the Departmentof Computer Science, CochinUniversity of Science andTechnology(CUSAT).Sheholds a Bachelor Degree inInformation Technology andMasters Degree in Computer

and Information Science.Her research area in-cludes image processing, secret sharing and secu-rity.

Dr.G.Santhosh Kumar re-ceived his MTech Degree inComputer and InformationScience from CUSAT, in 1999and PhD in Wireless SensorNetwork from Cochin Univer-sity of Science and Technol-ogy.

Currently he is working as an Associate Pro-fessor in CUSAT. He had more than 15 yearsof teaching experience. His research interestincludes Wireless Networks, Mobile Communica-tions and Software Architecture.

V P Binu is a ResearchScholar in the Departmentof Computer Applications,Cochin University of Scienceand Technology(CUSAT).Heholds a Bachelor Degree inComputer Science and Engi-neering and Masters Degree

in Computer and Information Science.His re-search area includes cryptography, secret sharingand security.

arXiv:1502.07993v1 [cs.CR] 26 Feb 2015 · 2018. 4. 25. · Cheque Truncation System(CTS) is an...

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