Image hatching for visual cryptography Essay

Abstract-Image hatching ( or non-photorealistic line-art ) is a technique widely applied in the printing or engraving of currency. Divers manners of coppice shots have antecedently been adopted for different countries of an image to make textures and shadowing. Because there is no uninterrupted tone within these types of images, we propose a multi-level strategy, which uses different textures based on a threshold degree. These textures are so applied to the different degrees and are so combined to construct up the concluding image. We propose a technique by which one can conceal a secret utilizing ocular cryptanalysis ( VC ) within the hatched images. Ocular cryptanalysis provides a really powerful agencies by which one secret can be distributed into two or more pieces known as portions. When the portions are superimposed precisely together, the original secret can be discovered without computing machine engagement.

Keywords-Visual cryptanalysis ; secret sharing ; image hatching


Ocular cryptanalysis ( VC ) is a powerful technique which combines the impressions of perfect cyphers and secret sharing in cryptanalysis with that of raster artworks. A binary image can be divided into portions which can be stacked together to about retrieve the original image. In this paper, we extend the impression of VC to that of hatched images. More- over, we propose the usage of this technique for authenticating hatched images by implanting a message inside which can merely be revealed if the corresponding secret hatched mask is superimposed upon the image.

Image hatching [ 1 ] in general is a series of similar shots which use assorted lengths, angles, common infinite, and other belongingss of lines to stand for parts of an image. These shots give deepness and form to the image. For illustration, a dark portion of an image would be represented by shots that are really near together. Conversely, a lighter subdivision of an image would be represented by shots that are farther apart. For any hatching strategy, the appropriate degree of item should be retained such that the image is still recog- nizable. Specific points such as vesture, facial characteristics, and looks should be unequivocally rendered. This type of non-photorealistic ( NPR ) line-art drawing has been extremely successful over the old ages, with its roots in line scratching [ 2 ] , classical pulling [ 3 ] and wood carving [ 4 ] .

The proposed technique of image hatching in this paper differs significantly from the bing techniques in how the concluding hatched images are generated. As with bing methods, the shots or textures utilized will make the right shadows and tones to convey a realistic image with appropriate shading. The strategy developed within this paper can be applied to any grayscale image in order to acquire a NPR hatched version ; illustrations are shown of human faces and physical edifices. We take these thoughts and widen them into the VC sphere and develop a fresh strategy to bring forth suited hatched images capable of concealing VC portions.

Figure 1 provides an illustration of our algorithm working on an image of the Birdsnest bowl. Figure 1 ( B ) and Fig- ure 1 ( degree Celsius ) provide a comparing between a real-time hatching technique [ 5 ] and our freshly proposed line-art based strategy. A more elaborate image of Lena is used subsequently within this paper to exemplify the procedure on a human face and to demo the versatility of our algorithm.

Image hatching for VC can be used for specialised image hallmark applications. For illustration, it can be used as a protection mechanism against counterfeiting of currency. Alone random masks can be employed to verify these specially created hatched images and used specifically in placing imitative polymer bills adopted world- broad. This security can be achieved through VC.

Related Work

Digital scratching techniques have been demonstrated [ 6 ] utilizing binary and color images. Ostromoukhov trades with 2D images and corresponds to work based on line-art [ 7 ] , [ 8 ] , [ 9 ] . It specifically deals with reproducing a human face every bit accurately as possible while keeping the traditional copperplate engraving manner. Other impressive pen-and-ink illustrations have been presented within [ 10 ] , [ 11 ] ; these use a coppice shot manner when reproducing the textures and shadowing, instead than a thinner line manner.

Real-time hatching techniques have besides been examined in 2001 [ 5 ] . The techniques discussed within [ 5 ] employ a tonic art map. This map scans the image or scene and creates a texture for it, after which a tone is generated which efforts to keep spacial and temporal coherency. However, this technique chiefly relies on 3D theoretical accounts for it to work right. A comparing between our technique and this real-time technique can be viewed in Figure 1.

Image sharing utilizing VC defines a strategy which is indistinguishable to that of general secret sharing [ 12 ] . In ( K, N ) image sharing, the image that carries the secret is split up into n pieces and the decoding is wholly unsuccessful unless at least K pieces are collected and superimposed. A ocular cryptanalysis strategy ( VCS ) provides a mechanism by which physically superposing two pieces ( known as portions ) of an image is able to firmly retrieve the secret.

The techniques developed within this paper aid to foster the security of printed images in that they provide an hallmark method. A fresh image hatching technique is besides presented which allows images to be converted to a manner which is similar to techniques presently in usage in today ‘s currency. The belongingss of these hatched images make them really suited for usage in concurrence with VC. They are halftone [ 13 ] images in that they are binary images. The distance between the pels indicates the textures and shadowing which are used to imitate the grey degrees.

Protection and hallmark of digital content, peculiarly printed images, is a enormously of import factor in today ‘s universe [ 14 ] , particularly when covering with currency. Securely protecting these points can be achieved utilizing VC. These VC techniques have been successfully applied utilizing watermark- ing techniques and cryptography.

Many ocular cryptanalysis strategies that have been developed, irrespective of image type, binary/halftone [ 15 ] , [ 16 ] , or color [ 17 ] , cover chiefly with sharing a individual secret. We use the thought of individual secret sharing within this paper. Further development of these strategies would increase the capableness of perchance concealing multiple secrets within these hatched images [ 18 ] , [ 19 ] , [ 20 ] . We besides use an image size invariant signifier of VC which allows the VC portions to be the same size as the original secret [ 21 ] .

There are three fresh results described in this paper:

( 1 ) Definition of a new technique which easy allows the creative activity of an NPR image, similar to that of a bank note ; ( 2 ) Definition of a method that will let us to utilize these hatched images as a screen image for the VC portions. This should let us to implant a secure portion within the hatched image ; ( 3 ) Extend the above definition to match to multiple hatched portions. Superimposing the hatched images should uncover the secret.

These techniques allow multiple, secure, proof and designation Markss on the screen image. If these VC portions can non be located or recovered, image meddling should be assumed and therefore the cogency of the image can non be trusted. The chief difference between this strategy and other halftone strategies is that our strategy uses a series of lines, the matching infinite between those lines gives the image the right form and shading, whereas other halftone images used in other strategies use dot bunch to accomplish the same effects.

The balance of this paper is set out as follows: Section III inside informations our parts and proposed techniques ; Section IV provides a security analysis of the proposed strategy ; the consequences are displayed in Section V ; the concluding decisions are drawn in Section VI.

OUR Contribution

Image Hatching

Our proposed strategy consists of eight different textures ( line manners ) which are used for the assorted shadowing effects. Let S stand for the set of textures, such that Si? S where Si is one of the texture forms and i = 1, 2, . . . , 8. Figure 2 illustrates these textures.

The following measure involves taking multiple threshold degrees of the original grayscale image to let the textures to be applied. Because there are eight different textures, we must besides obtain eight different threshold degrees from the image to which each of the shots can be applied.

Let Palestine Islamic Jihad & A ; epsilon ; P, P is the set of all pels and Palestine Islamic Jihad = Let pij ? P, P is the set of all pels and Palestine Islamic Jihad =

0, . . . , 255 where Palestine Islamic Jihad represents the pels grayscale value,

I = 1, 2, . . . , W and J = 1, 2, . . . , H. W and H represent the images width and height severally. For illustration, the pel at coordinate place ( 0, 0 ) with the grayscale value 34 would be represented like this: p0,0 = 34.

Our threshold map examines P eight different times based on a different grayscale degree each clip, tk & A ; epsilon ; T, k = 1, 2, . . . , 8, tk represents the current grayscale threshold of the image. If 0? Palestine Islamic Jihad & A ; lt ; 32k, draw a black pel, otherwise pull a white pel. This procedure is performed for each grayscale threshold. For illustration, grayscale degree K = 4 would fall between: 0? Palestine Islamic Jihad & A ; lt ; 128 which corresponds to the threshold image within Figure 3 ( vitamin D ) .

First, the eight hatching textures from Figure 2 are created. The textures are so applied to the thresholds utilizing Eq. ( 1 ) . This works as follows: each of the textures need to be applied to its matching threshold so as to make the set of thresholds with their corresponding textures ( Figure 4 ) . The first brace are taken s1 and t1, and Eq. ( 1 ) is applied. At the pel degree, this operation can be represented mathematically, where V is the pel value returned, soap is the largest pel value, si represents the pel values in the texture image and Ti represents the pel values in the threshold image.

( max -ti )

Image Hatching with VC

Traditional VC portions are really effectual in footings of secret sharing, but pixel enlargement tends to be a job. Pixel enlargement occurs due to how the VC portions are created. Typically one pel is expanded into a 2 – 2 block of pels, which is used to stand for the original pel. This consequences in the concluding portions being twice the size of the original secret after encoding. Size invariant portions have the potency for better consequences, they have no pixel enlargement and offer quality similar to that of the traditional strategies. We utilize the strategy proposed in [ 21 ] when making the portions for our strategy.

Once the hatched image has been generated, a secret of the same size is chosen. The secret is non required to be a hatched image, any secret can be used. The size invariant VC strategy is applied to the secret in order to bring forth the two portions. To implant the first portion successfully within the hatched image we need to change it. This involves cut downing its overall pel denseness. This decrease in pixel denseness is a trade-off between security and visually being able to conceal the portion within the hatched image. It lowers the cured secret ‘s overall contrast but allows the embedded hatched image to stay invisible. Contrast is an highly of import portion of any VC strategy [ 22 ] , [ 23 ] because it determines the visibleness of the cured secret.

Reducing the portions denseness involves cutting or taking perpendicular or horizontal strips from the first portion image. This allows the portion to be embedded, without falsifying the hatched image excessively significantly, while maintaining its secure belongingss and retaining adequate informations in order to successfully retrieve the secret. This cutting procedure removes specific pels, either at random, or on a row or column footing. This allows for easy interpolation of the portion into the hatched image without dramatically changing the overall hatched images quality.

V = max – ( max -si ) – soap

Three separate strategies are defined here for utilizing the 2nd portion in order to retrieve the secret. The first, used in Figure 7, leaves the 2nd portion unchanged, ensuing in a non-hatched random mask for the hatching screen image and its embedded VC portion. This provides an overall darker contrast after the secret has been revealed. The 2nd strategy, illustrated in Figure 8, involves making a secure hatched mesh. Forms from S are chosen, viz. s6 and s8 and are so applied to the 2nd portion. This hatched mesh portion is used to retrieve the embedded secret. The concluding strategy is presented in Figure 9. Each portion is embedded into a hatched image, utilizing the same film editing procedure described above. Superimposing these hatched images reveals the secret. Figure 5 provides a flow chart of these prospective strategies.


The security of our proposed strategy rests chiefly with VC but besides the screen images. First, our chosen size invariant VC strategy is unafraid in that given any sum of sub-pixels from a individual portion, it is impossible to state if the corresponding portions sub-pixels represent a black or a white pel before superposing them. This means that even if the complete VC portion form is discovered within the screen image, working out its matching portion is extremely hard. Traditional VC portions can besides be employed within this strategy. This does intend that the secrets have to be half the size of the hatched image in footings of dimensions ( due to the pixel enlargement ) but it besides means the security of this strategy holds up really good, which has been good documented in the literature [ 24 ] .

Nothing about the secret can be deduced based on analysis of either the screen image or the telling portion. After the portion has been embedded, certain pels overlap, this besides impedes analysis because it remains unsure if that overlapped pixel belongs to the original screen image or the existent embedded portion itself.

Second, the hatched image is visually delighting which helps to pull attending off from any encoding or resound the embedded portions may bring forth. This alleviates any suspi- cion that encoding has taken topographic point, therefore farther increasing the overall secretiveness of the embedded portions by increasing their imperceptibility.


In this subdivision, we provide the consequences and commentary on each of the expected results discussed antecedently in Section II. All codification was developed in Python 2.5 utilizing the Python Imaging Library 1.1.6.

Figure 6 ( a ) shows the original Lena image, its binary halftone equivalent is in Figure 6 ( B ) ( created utilizing Floyd- Steinberg dithering ) and the freshly created hatched image based on our proposed strategy is located in Figure 6 ( degree Celsius ) . Notice the different contours and line waies to give the image the right deepness and feel. The dark parts of the image demo up right in that they have a really thick texture form applied to them. The brighter parts have a lighter texture form on them so that they do non demo up wholly white. This is really similar to the scratching techniques discussed antecedently. All the specific facial characteristics such as the oral cavity, nose, and eyes are all right displayed along with the chapeau and plumes. The frame of the mirror is besides clearly seeable and defined. This supports our first expected result.

Figure 7 and Figure 8 high spot expected outcome two and provides the consequences. The hatched screen image is still really legible with the embedded VC portion. The 2nd portion can so be used to retrieve the secret. This provides a really utile technique for practical applications in footings of confirmation and designation of images. This type of technique could be adapted to look into the cogency of currency because of its secure belongingss antecedently discussed.

Figure 9 shows how we achieved expected outcome three. Two VC portions are hidden within two separate hatched images. Figure 9 ( a ) and 9 ( B ) illustrate the concluding hatched images with the embedded portions. The end point secret after superposing each of these hatched images can be viewed in Figure 9 ( degree Celsius ) . The secret is seeable, nevertheless due to the nature of this strategy, the contrast suffers when the secret is recovered. The text is clearly seeable, but this would be a possible country for betterment.


In this paper, we have developed a fresh hatching strategy for images which embed a secret utilizing VC. This technique can be used for image hallmark. For image hatching, bring forthing similar forms to those used in the engraving and printing of currency can be accomplished. Generating these hatched images utilizing a threshold based attack has proved to be really effectual and easy to implement. One of the cardinal strengths of the strategy is that it can take a battalion of images and use these hatching manners to them. No specific type of image is required. This would let for easy application in the currency sphere with regard to bring forthing suited images based on current up-to-date techniques.

Using these hatched forms, we have described assorted ways of implanting basic VC portions within them. The point forms are little plenty so that they can be hidden within similar parts of an appropriate image, but besides remain really legible and clear after the secret recovery has taken topographic point.

This type of secret embedding could hold assorted po- tential secure applications, particulary within the banking industry. Protecting high value checks, for hallmark and designation intents utilizing our techniques could easy be applied.


  1. G. Elber, “ Line art illustrations of parametric and inexplicit signifiers, ” IEEE Transactions on Visualization and Computer Graphics, vol. 4, no. 1, pp. 71-81, 1998.
  2. W. M. Ivins, How Prints Look, Photographs with Commen- tary, revised erectile dysfunction. Boston: Beacon Press, 1987.
  3. — , Prints and Visual Communication, 8th printing. MIT Press, 1992.
  4. P. N. Hasluck, Manual of Traditional Wood Carving. New York: Dover Publications, 1977.
  5. E. Praun, H. Hoppe, M. Webb, and A. Finkelstein, “ Real-time hatching, ” in SIGGRAPH ’01, New York, NY, USA, 2001, pp. 581-586.
  6. V. Ostromoukhov, “ Digital facial engraving, ” in SIGGRAPH ’99, New York, NY, USA, 1999, pp. 417-424.
  7. G. Elber, “ Line Art Rendering via a Coverage of Isoparamet- ric Curves, ” IEEE Transactions on Visualization and Com- puter Graphics, vol. 1, no. 3, pp. 231-239, September 1995.
  8. — , “ Line Illustrations in Computer Graphics, ” The Visual Computer, vol. 11, no. 6, pp. 290-296, June 1995.
  9. — , “ Line Art Illustrations of Parametric and Implicit Forms, ” IEEE Transactions on Visualization and Computer Graphics, vol. 4, no. 1, pp. 71-81, January 1998.
  10. M. Salisbury, C. Anderson, D. Lischinski, and D. H. Salesin, “ Scale-dependent reproduction of pen-and-ink illustrations, ” in SIGGRAPH ’96, New York, NY, USA, 1996, pp. 461-468.
  11. M. P. Salisbury, S. E. Anderson, R. Barzel, and D. H. Salesin, “ Synergistic pen-and-ink illustration, ” in SIGGRAPH ’94, New York, NY, USA, 1994, pp. 101-108.
  12. A. Shamir, “ How to portion a secret, ” Communications of the ACM, vol. 22, no. 11, pp. 612-613, 1979.
  13. D. L. Lau and G. R. Arce, Modern Digital Halftoning. Marcel Dekker, 2000.
  14. N. Memon and P. W. Wong, “ Protecting digital media con- collapsible shelter, ” Communications of the ACM, vol. 41, no. 7, pp. 35-43, 1998.
  15. G. Ateniese, C. Blundo, A. D. Santis, and D. R. Stinson, “ Extended strategies for ocular cryptanalysis, ” Theoretical Computer Science, vol. 250, pp. 1-16, June 1996.
  16. Z. Zhou, G. R. Arce, and G. D. Crescenzo, “ Halftone vi- sual cryptanalysis, ” IEEE Transactions on Image Processing, vol. 15, no. 8, pp. 2441-2453, August 2006.
  17. Y. C. Hou, C. Y. Chang, and S. F. Tu, “ Ocular cryptanalysis for colour images based on halftone engineering, ” Proceedings of International Conference on Image, Acoustic, Speech and Signal Processing, Part 2, 2001.
  18. J.-B. Feng, H.-C. Wu, C.-S. Tsai, Y.-F. Chang, and Y.-P.
  19. Chu, “ Ocular secret sharing for multiple secrets, ” Pattern Recognition, vol. 41, no. 12, pp. 3572-3581, 2008.
  20. H.-C. Hsu, T.-S. Chen, and Y.-H. Lin, “ The annular shadow image engineering of ocular cryptanalysis by using diverse revolving angles to conceal the secret sharing, ” Networking, Sens- ing and Control, vol. 2, pp. 996-1001, 2004.
  21. S. J. Shyu, S.-Y. Huang, Y.-K. Lee, R.-Z. Wang, and K. Chen, “ Sharing multiple secrets in ocular cryptanalysis, ” Pattern Recognition, vol. 40, no. 12, pp. 3633-3651, 2007.
  22. R. Ito, H. Kuwakado, and H. Tanaka, “ Image size invariant ocular cryptanalysis, ” Institute of Electronic, Information and Communication Engineers Transactions, vol. E82-A, no. 10, pp. 2172 – 2177, October 1999.
  23. C. Blundo, P. D’Arco, A. D. Santis, and D. R. Stinson, “ Contrast optimum threshold ocular cryptanalysis strategies, ” SIAM Journal on Discrete Mathematics, vol. 16, no. 2, pp. 224-261, 2003.
  24. C.-N. Yang, C.-C. Wang, and T.-S. Chen, “ Real perfect contrast ocular secret sharing strategies with reversing, ” in ACNS, 2006, pp. 433-447.
  25. A. De Bonis and A. De Santis, “ Randomness in secret sharing and ocular cryptanalysis strategies, ” Theoretical Computer Science, vol. 314, no. 3, pp. 351-374, 2004.