Those are generalizations, but should allow the reader to understand, once again, the main difficulties involved in the design of digimarks systems and should also as the natural preliminaries to the following paragraph discussing the difficulties of that technology.
Perceptual Transparency :-Use characteristics of the Human Visual System to assure that the watermark is not visible under typical viewing conditions. Basically, it means that a watermark image should not seem any different form the original (unmarked) one; i.e. one should not notice any degradation in the perceived quality. Other types of the watermarks are meant to be visible, but in most applications they are not and this is why we treat transparency as a basic requirement of digital watermarking.
Robustness:- This describes weather the watermark can be reliably detected after media operations, format conversions, rotations, scaling. For e.g. The mosaic tool attacks the robustness of the watermarking algorithms with geometrical distortions. Copyright, fingerprinting and copy control watermarks should have high robustness. Annotation
watermarks should be robust against common editing processes.
Capacity:-It describes how many bits of information can be embedded in to a multimedia media. It also addresses the possibility of embedding multiple watermarks in one document in parallel for e.g. Double Watermarking ( means that the same image is watermarked twice, using different watermarks. One watermark may denote the owner while the second watermark will denote the customer.) Generally annotation watermarks have the highest capacity requirements.
Security:-It describes weather the embedded watermarked information can be removed beyond reliable detection by targeted attacks. Based on knowing the embedded algorithm and the detector- except the keys- add the knowledge of at least one watermarked data.
Security evaluates hackers can easily bypass low security watermarks. All watermarks except annotation should provide high security The basis of watermarking security should lie on Kerckhoff’s assumption that one should assume that the method used to encrypt the data is known to the unauthorized party
Specificity:- The watermark should be universal, i.e. applicable to images as well as audio and video media infract that has been found nt to be true; the general might be the same in multiple applications but, in watermarking, one size dose not fit all.
A lot of difficulties are encountered while trying to define the ideal watermarking scheme for a
particular application
- In highly compresses JPEG images, there is a limited amount of data that can be used to inser digital watermarks
- The introduction of artifacts by compression techniques usually destroys watermarks easily.
- Robustness and Transparency are two fundamentally apposed requirements; a trade off betwee the two must then be made.
The Watermark Embedding Process:
The process of mapping a large (possibly infinite) set of values to smaller set is called quantization. Every possible value of the host image pixel is quantized using a quantization function (Q ()) to a small set of values, equal in number to the size of the LUT. The table then maps the quantized value to 1 or 0. Lookup () function simply returns a 0 or 1 depending upon the input index, Lookup(x) = value in LUT at index x The LUT () function takes the pixel value of the original Assume, vi is the original coefficient, vi is the marked one, bi is the bit to be embedded and LUT () is the mapping by the Look-up Table. Then the process altering a coefficient in the original image can be
written as the following formula:
procedure is depicted in the Block Diagram in Figure 5.
For finding the corresponding pixel position in the original image, a prime constant N is chosen. The corresponding nth pixel in the original image for the ith pixel of the watermark is given by (i * N)%P. However, if the pixel belongs to the range of the RoI range or if the modified value of the pixel obtained from LUT belongs to the RoI range, then it is not altered. Therefore, the corresponding pixel for bi is actually given by [(i+j)*N]%P, where j is the number of pixels which has been to be left unaltered as they belong to the RoI. Thus the original image has been watermarked when the corresponding original image pixel for each of the pixels in the watermark image has been modified.
The Watermark Extraction Process:-
The watermark can be extracted easily on the production of the watermarking key K. The size of the watermark can either be fixed by the organization or it can be obtained from the watermarking key by modifying the function Key (). The watermark W is assumed to be fixed here. The value of W and the size of the watermarked image together determine the value of N uniquely. LUT can be obtained from the key K and the value of N. Once N and LUT are known, the pixel values of the watermark can be extracted from the LUT taking into consideration the pixel values left unaltered, as either the pixel values belong to the RoI or the modified values of the pixels as obtained from table-lookup belong to the RoI. The table can be looked up as bi ¢ = LUT (vi) where bi is the extracted bit representing the ith pixel of the watermark and vn is the corresponding pixel in the original image. As in the case of embedding, the value of n is given by [(i+j)*N]%P, where j = the number of pixels which has been left unaltered as they belonged to the RoI. The method is outlined in the Block Diagram shown in Figure below
used to check if the image has been tampered with.
An Example
A JPEG compressed satellite image of the western region of the Indian subcontinent of size
578x494(P= 285532) is shown in Figure 9(a). The watermark of 100x100 size is shown in Figure 9(b).
 |
| Fig 9b Binary Watermark |
Suppose the image is to be sold to an organization interested in studying the sea region, therefore, the Region of Interest is the blue watery areas visible in the image. In JAVA, the RGB color model represents each pixel as an integer (4 bytes) with the Alpha, Red, Green and Blue (0xAARRGGBB). The first byte or the alpha value denotes the degree of transparency, 0 for a fully transparent and 255 for a fully opaque image. Thus, the value of alpha is 255 for all the pixels in the images used in this algorithm. The integer representing a pixel is being referred to as the “value” of that pixel. It is found that the pixel value range in which the salty areas lie is: -13413007 to -9068625. The values -13413007 to -9068625 are the minimum and maximum values of a pixel expected in the salty region.
The Look-up Table used is a 512 bit binary pseudorandom sequence as shown in Figure 4. The value of N (any Prime Number) taken is 29. The quantization function (Q ()) used is a simple modulo function with respect to the size of the table, i.e. Q(x) = abs(x%S) where x is the input coefficient, S is the size of the LUT and abs () is the absolute value function. The key function Key () is the concatenation function with the Lookup Table along with the prime number N. With these specifications, the image in Figure 9(a) has been watermarked to obtain the image shown in Figure 7. The difference image is shown in Figure 10(b).
It is not difficult to see that the areas where the sea region is present have not been distorted still the watermark has been embedded uniformly in the other parts of the image. The algorithm encountered 4346 pixel values that belong to the Region of Interest and therefore, has been skipped. The value of the index used to locate the pixel in the host image in which the watermark bit has to be embedded (i.e. the value of n) wrapped around just once over the pixels of the original image. The watermarking key obtained is:
3d33e3b1-363b2476-5846a75b-5552a11b-612f5eef-644f31eb-7a9ac864-5c8bc62e-2e5e52f3-8ed61add-3ceee95e-2245dc46-625a6fb1-3cf7dddd-0999a6e4-390c7d53-0000001d
The watermark of Figure 9(b) can be easily extracted from the watermarked image shown in Figure 10(a) with the help of this key.
Conclusion
An exhaustive list of watermarking applications is of course impossible. However, it is interesting to note the increasing interest watermarking technologies. Especially applications related to copy protection of printed media are very promising. Examples here include Watermarking of
Satellite Images.
A novel watermarking scheme has been presented also for copyright control of satellite images. The proposed scheme can be used to watermark satellite images without distorting the vital regions that are of interest to the customer. Hence, the value of the image is preserved. At the same time, the ownership of the satellite image can be proven whenever required on the production of the key by the legal owner, thereby, keeping a check on illegal copying of the copyrighted image. It s yet to be seen whether algorithm can be improved by relaxing constraints, double watermarking and extension of LUT as the satellite image is generally much larger than the watermark image. In addition to technological developments, marketing and business issues are extremely important and require in-depth analysis and strategic planning. It is very important to prepare the industry to the usage of digital watermarks and to convince them of the added value their products can gain if they employ digital watermarking technologies
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