CN111242825A - ENC electronic nautical chart zero-watermarking method based on water depth characteristics - Google Patents
ENC electronic nautical chart zero-watermarking method based on water depth characteristics Download PDFInfo
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Abstract
The ENC electronic nautical chart zero-watermarking method based on the water depth features comprises a zero-watermarking structure and a zero-watermarking extraction inspection method, not only is certain data (space) disturbance caused to electronic nautical chart data by a reversible watermarking algorithm of the space features overcome, but also the resistance of nondestructive watermarking algorithm precision reduction of the attribute features is improved.
Description
Technical Field
The invention relates to the technical field of ocean mapping.
Background
The ENC electronic nautical chart zero-watermarking technology belongs to a digital watermarking technology in a special application range, and is widely applied to the fields of ENC electronic nautical chart copyright protection or content authentication and the like.
Currently, researches on a two-dimensional electronic chart digital watermarking algorithm mainly include a reversible watermarking algorithm based on spatial characteristics, a lossless watermarking algorithm based on attribute characteristics and a digital watermarking algorithm based on semantics. The reversible watermark algorithm based on the spatial characteristics is characterized in that the electronic chart is essentially formed by continuously changing and evolving discrete vector nodes, embedding nodes of the watermark can be obtained by analyzing the evolution process of the chart, embedding of the reversible watermark algorithm is further realized, in order to avoid causing overlarge data disturbance to the electronic chart, the embedding process of the watermark needs to be kept within a certain disturbance range, and after watermark information is successfully extracted, similarity calculation is carried out on the digital watermark information. The lossless watermark algorithm based on the attribute characteristics adopts a zero-bit dynamic lossless watermark implementation method based on a gradient algorithm, uses a zero-bit expansion technology for watermark processing, is combined with an embedding point selection technology of a digital watermark gradient algorithm, and has better watermark invisibility and robustness. The digital watermarking algorithm based on the semantics, the use target of the semantic watermarking is limited in a legal user, the propagation environment is controlled, on the basis, the authority of each user is limited, the user cannot initiate direct attack on the semantic watermarking before map data is opened, meanwhile, the semantic watermarking adopts a redundant embedding mode, some redundant vertexes are embedded into a map before the map is distributed, the authority watermarking is extracted before the user uses the map, the redundant vertexes are synchronously removed, and the normal use of the map is not interfered.
The three algorithms described above still have many disadvantages: a reversible watermark algorithm based on spatial characteristics causes a certain data (spatial) disturbance range to the electronic chart data; the lossless watermarking algorithm based on the attribute characteristics is difficult to add zero-bit watermarks into the ENC electronic nautical chart, because the unit used by the position in the S57 specification is latitude and longitude coordinates and is converted into an integer value through a multiplier factor COMF, and meanwhile, the precision reduction resistance, the format conversion resistance and the interpretation attack resistance are poor. The digital watermarking algorithm based on the semantics emphasizes the adoption of an image matching technology, the digital watermarking of wider semantic information needs to be researched, meanwhile, the chart updating ER is the most common operation, and the correctability of ENC chart data is insufficient. In terms of experimental environment, the three algorithms all use MapInfo software, and the main forming form of the electronic chart is an SHP file.
Disclosure of Invention
In order to overcome the defects of the three methods, the invention provides an ENC electronic nautical chart zero-watermarking technology based on water depth characteristics.
The technical scheme adopted by the invention for realizing the purpose is as follows: a water depth feature-based ENC electronic nautical chart zero watermark method comprises a zero watermark construction method and comprises the following steps:
the method comprises the following steps: preprocessing the ENC electronic chart to obtain water depth data;
step two: constructing a Delaunay triangulation network for the water depth data constructing the zero watermark, extracting a slope characteristic line by utilizing water depth interpolation, and judging the slope characteristic between the point pairs on the line according to the extracted characteristic line as a skeleton line so as to extract characteristic points;
step three: selecting a proper threshold value for the extracted feature points to carry out point constraint blocking, and sequencing the water depth points in each block through ZigZag to further obtain a longitude and latitude coordinate binary sequence of the water depth points, so as to ensure that the length of the coordinate binary sequence in each block is greater than that of the watermark sequence;
step four: performing Arnold scrambling on an original watermark image to obtain an encrypted watermark image, and performing grouping conversion to obtain a watermark sequence;
step five: carrying out bit-filling XOR operation on the longitude and latitude coordinate binary sequence and the watermark sequence to obtain a zero watermark image, namely a zero watermark; step six: storing the zero watermark image generated by each block and the original watermark image;
the zero watermark extraction and inspection method comprises the following steps:
the method comprises the following steps: preprocessing an ENC electronic chart to be detected to obtain water depth data;
step two: constructing a Delaunay triangulation network for the water depth data, and further judging and extracting water depth feature points by extracting a slope characteristic line through water depth interpolation;
step three: performing point constraint blocking on the extracted feature points, and sequencing the water depth points in each block through ZigZag to obtain a binary sequence of longitude and latitude coordinates of the water depth points;
step four: grouping and converting the watermark images to obtain a watermark sequence, performing complementary XOR operation on the longitude and latitude coordinate binary sequence and the watermark sequence, extracting a plurality of encrypted watermark images according to the size of the original watermark, and performing Arnold reverse scrambling to obtain a watermark image of data to be detected;
step five: comparing and verifying the extracted watermark images with the original watermark image, and measuring the similarity of the two images by using the normalized correlation coefficient NC value so as to judge the copyright ownership of the data to be detected.
In the third step of zero watermark construction, the unit used in the position in the ENC electronic nautical chart is decimal degree converted into integer, the integer value of the converted coordinate is encoded by binary system, and the integer value before the precision effective bit is converted into binary system.
In the fourth and fifth zero watermark construction steps, the watermark is encrypted by adopting an Arnold conversion mode, picture data Arnold with equal length and width are scrambled, and the Arnold conversion formula is as follows:
and N is the length and width of the picture, X and Y are the horizontal and vertical coordinates of one point on the original image, another point coordinate X 'and Y' is formed through transformation, the transformed image is subjected to binarization processing, and the binary sequence of the coordinates after the transformation and the binary sequence of the coordinates after the block are subjected to complementary exclusive OR operation to obtain a zero watermark image.
In the fourth step of zero watermark extraction and inspection, when the extracted scrambled image is subjected to reduction processing, an inverse matrix is obtained for the forward replacement formula to obtain an inverse transformation formula of Arnold replacement, and the original image is directly formed through the inverse transformation formula, wherein the inverse transformation formula of Arnold transformation is as follows:
in the step five of zero watermark extraction and inspection, whether the watermark data has copyright authentication is judged by comparing the similarity value with a set threshold value, and the calculation formula of the similarity (NC) is as follows:
wherein W (i, j) represents the pixel value at (i, j) in the original watermark data, W' (i, j) represents the pixel value at (i, j) in the watermark data extracted from the vector chart, m, n represents the values of the row and column of the watermark picture data,
when NC is 1, the extracted watermark picture data is completely the same as the original watermark picture data, and the picture is not changed after being attacked; when the NC value is between 0 and 1, the closer to 1, the higher the data similarity is, and the watermark robustness is strong; and conversely, the lower the similarity is, the lower the watermark robustness is, wherein the NC value is 0.7 as the threshold value for identifying the watermark.
In the step five of zero watermark extraction and inspection, the comparison and verification are measured by the structural similarity SSIM, and the SSIM is as follows:
SSIM(W,W')＝l(W,W')c(W,W')s(W,W')#(4)
where W is the watermark image, W' is the extracted watermark image,
the closer the value of SSIM is to 1, the more similar the two images are and the better the quality of the images is.
The ENC electronic nautical chart zero-watermarking method based on the water depth features overcomes certain data (space) disturbance of a reversible watermarking algorithm of the space features on electronic nautical chart data, and improves the resistance of approximately reducing the precision of a lossless watermarking algorithm of the attribute features.
Drawings
FIG. 1 is a flow chart of the ENC electronic nautical chart zero watermark construction of the present invention.
FIG. 2 is a flow chart of ENC electronic nautical chart zero watermark extraction and inspection.
Fig. 3 is a schematic diagram of the operation platform of the SuperMap software.
Fig. 4(a) is a schematic diagram of an original watermark.
Fig. 4(b) is a schematic diagram of the watermark after the watermark image Arnold is scrambled for 1 time.
Fig. 4(c) is a schematic diagram of the watermark after 2 times of Arnold scrambling of the watermark image.
Fig. 4(d) is a schematic diagram of the watermark after the watermark image Arnold is scrambled 10 times.
Fig. 4(e) is a schematic diagram of the watermark after the watermark image Arnold is scrambled 20 times.
Fig. 4(f) is a schematic diagram of the watermark after the watermark image Arnold is scrambled for 30 times.
Detailed Description
The invention discloses a water depth feature-based ENC electronic nautical chart zero watermark method, which comprises a zero watermark structure and zero watermark extraction inspection, wherein the zero watermark structure is shown in figure 1, and the method comprises the following steps:
the method comprises the following steps: preprocessing the ENC electronic nautical chart through Supermap hyper-map software to obtain water depth data;
step two: the method comprises the steps of constructing a Delaunay triangulation network for water depth data with zero watermarks, extracting a slope characteristic line by utilizing water depth interpolation, judging slope characteristics between point pairs on the line according to the extracted characteristic line serving as a skeleton line, further extracting characteristic points, wherein the slope characteristic line is a concept line used for describing a water depth point slope relation tree and is a transition virtual connection line for providing judgment basis for characteristic shallow point extraction, and limiting conditions are that a threshold interval is selected for depth values of set water depth data, namely water depth data in a closed equal-depth area on a graph are taken as a class, so that influence of data outside the interval on data in the interval is avoided. After a triangulation network is constructed and a characteristic line is extracted, the characteristic line is used as a skeleton line of the submarine topography, and the slope direction characteristic between the point pairs on the line is judged, namely, the shallowest point and the relatively shallow point in the water depth data are regarded as 'characteristic shallow points' for extraction;
step three: selecting a proper threshold value for point constraint blocking of the extracted characteristic points, sequencing the water depth points in each block through ZigZag, further obtaining a longitude and latitude coordinate binary system sequence of the water depth points, ensuring that the length of the coordinate binary system sequence in each block is larger than that of the watermark sequence, converting the position used unit in the ENC electronic nautical chart into an integer decimal degree, coding the converted coordinate integer value by using the binary system, converting the integer value before the precision effective bit (discarding the two bits) into the binary system for resisting precision reduction, sequencing through ZigZag and recording the longitude and latitude binary system sequence in each block, and ensuring that the longitude and latitude binary system sequence in each block is sequenced and recorded through ZigZagThe length of the coordinate sequence is larger than that of the watermark sequence, and the longitude and latitude of a single water depth point pass through a multiplier factor COMF (10)7) Converting into integer, discarding last (two) bits and using binary coding within the precision allowable range;
step four: performing Arnold scrambling on an original watermark image to obtain an encrypted watermark image, performing grouping conversion to obtain a watermark sequence, and encrypting the watermark by using an Arnold conversion mode, as shown in FIG. 4;
step five: and carrying out bit-complementing XOR operation on the longitude and latitude coordinate binary sequence and the watermark sequence to obtain a zero watermark image, namely a zero watermark, and carrying out Arnold scrambling on picture data with the same length and width to simplify calculation. The Arnold transformation formula is:
n is the size of the length and the width of a picture, X and Y are the horizontal and vertical coordinates of one point on an original image, another point coordinate X 'and Y' is formed through transformation, the transformed image is subjected to binarization processing, and the binary sequence of the partitioned coordinates is subjected to complementary XOR operation to obtain a zero watermark image, the larger N is, the larger the represented watermark information quantity is, the longer the cycle period T is, and the more users of the chart are mapped through scrambling times (keys);
step six: and storing the zero watermark image generated by each block and the original watermark image to a copyright protection center (IPR), and adding a time stamp with legal effectiveness to resist interpretation attack.
The zero watermark extraction test is shown in fig. 2 and comprises the following steps:
the method comprises the following steps: preprocessing an ENC electronic chart to be detected to obtain water depth data;
step two: constructing a Delaunay triangulation network for the water depth data, and further judging and extracting water depth feature points by extracting a slope characteristic line through water depth interpolation;
step three: performing point constraint blocking on the extracted feature points, and sequencing the water depth points in each block through ZigZag to obtain a binary sequence of longitude and latitude coordinates of the water depth points;
step four: the method comprises the following steps of performing grouping conversion on watermark images to obtain a watermark sequence, performing complementary XOR operation on a longitude and latitude coordinate binary sequence and the watermark sequence, extracting a plurality of encrypted watermark images according to the size of an original watermark, performing Arnold inverse scrambling to obtain a watermark image of data to be detected, performing reduction processing on the scrambled image after extraction, if the original image is replaced n times, performing T-n iterations to recover the original image, obviously depending on a forward formula with too large operation amount, solving an inverse matrix of the forward replacement formula to obtain an inverse transformation formula of Arnold replacement, and directly performing n times of transformation through the inverse transformation formula to form the original image, wherein the inverse transformation formula of Arnold transformation is as follows:
step five: comparing and verifying a plurality of extracted watermark images with an original watermark image, measuring the similarity of the two images by using a Normalized correlation coefficient NC (Normalized correlation) value, further judging the copyright attribution of the data to be detected, testing the robustness of the embedded digital watermark, calculating the Normalized correlation coefficient (Normalized correlation, NC) of the extracted watermark data and the original watermark data after carrying out geometric transformation (translation, rotation and scaling), map cutting, data deletion and addition on a vector chart, and comparing and judging whether the watermark data has copyright certification or not through the similarity value and a set threshold value. The calculation formula of the similarity (NC) is as follows:
wherein W (i, j) represents the pixel value at (i, j) in the original watermark data, W' (i, j) represents the pixel value at (i, j) in the watermark data extracted from the vector chart, m, n represents the values of the row and column of the watermark picture data,
when NC is 1, the extracted watermark picture data is completely the same as the original watermark picture data, and the picture is not changed after being attacked; when the NC value is between 0 and 1, the closer to 1, the higher the data similarity is, and the watermark robustness is strong; the lower the similarity, the less robust the watermark is. Where the NC value typically takes 0.7 as the threshold for identifying the watermark.
The comparison verification can also be measured by Structural Similarity (SSIM), which is defined as:
SSIM(W,W')＝l(W,W')c(W,W')s(W,W')#(4)
where W is the watermark image, W' is the extracted watermark image,
the closer the value of SSIM is to 1, the more similar the two images are and the better the quality of the images, generally speaking, the SSIM value is greater than 0.5, and one can accept the quality of the images.
While the invention has been described with reference to exemplary embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from the essential scope thereof. Therefore, it is intended that the invention not be limited to the particular embodiment disclosed, but that the invention will include all embodiments falling within the scope of the appended claims.
Claims (7)
1. An ENC electronic nautical chart zero-watermarking method based on water depth features is characterized by comprising the following steps: the method comprises a zero watermark construction method, and comprises the following steps:
the method comprises the following steps: preprocessing the ENC electronic chart to obtain water depth data;
step two: constructing a Delaunay triangulation network for the water depth data constructing the zero watermark, extracting a slope characteristic line by utilizing water depth interpolation, and judging the slope characteristic between the point pairs on the line according to the extracted characteristic line as a skeleton line so as to extract characteristic points;
step three: selecting a proper threshold value for the extracted feature points to carry out point constraint blocking, and sequencing the water depth points in each block through ZigZag to further obtain a longitude and latitude coordinate binary sequence of the water depth points, so as to ensure that the length of the coordinate binary sequence in each block is greater than that of the watermark sequence;
step four: performing Arnold scrambling on an original watermark image to obtain an encrypted watermark image, and performing grouping conversion to obtain a watermark sequence;
step five: carrying out bit-filling XOR operation on the longitude and latitude coordinate binary sequence and the watermark sequence to obtain a zero watermark image, namely a zero watermark;
step six: and storing the zero watermark image generated by each block and the original watermark image.
2. The ENC electronic nautical chart zero-watermarking method based on the water depth feature of claim 1, wherein: the zero watermark extraction and inspection method comprises the following steps:
the method comprises the following steps: preprocessing an ENC electronic chart to be detected to obtain water depth data;
step two: constructing a Delaunay triangulation network for the water depth data, and further judging and extracting water depth feature points by extracting a slope characteristic line through water depth interpolation;
step three: performing point constraint blocking on the extracted feature points, and sequencing the water depth points in each block through ZigZag to obtain a binary sequence of longitude and latitude coordinates of the water depth points;
step four: grouping and converting the watermark images to obtain a watermark sequence, performing complementary XOR operation on the longitude and latitude coordinate binary sequence and the watermark sequence, extracting a plurality of encrypted watermark images according to the size of the original watermark, and performing Arnold reverse scrambling to obtain a watermark image of data to be detected;
step five: comparing and verifying the extracted watermark images with the original watermark image, and measuring the similarity of the two images by using the normalized correlation coefficient NC value so as to judge the copyright ownership of the data to be detected.
3. The ENC electronic nautical chart zero-watermarking method based on the water depth feature of claim 1, wherein: in the third step of zero watermark construction, the unit used in the position in the ENC electronic nautical chart is decimal degree converted into integer, the integer value of the converted coordinate is encoded by binary system, and the integer value before the precision effective bit is converted into binary system.
4. The ENC electronic nautical chart zero-watermarking method based on the water depth feature of claim 1, wherein: in the fourth and fifth zero watermark construction steps, the watermark is encrypted by adopting an Arnold conversion mode, picture data Arnold with equal length and width are scrambled, and the Arnold conversion formula is as follows:
and N is the length and width of the picture, X and Y are the horizontal and vertical coordinates of one point on the original image, another point coordinate X 'and Y' is formed through transformation, the transformed image is subjected to binarization processing, and the binary sequence of the coordinates after the transformation and the binary sequence of the coordinates after the block are subjected to complementary exclusive OR operation to obtain a zero watermark image.
5. The ENC electronic nautical chart zero-watermarking method based on the water depth feature of claim 2, wherein: in the fourth step of zero watermark extraction and inspection, when the extracted scrambled image is subjected to reduction processing, an inverse matrix is obtained for the forward replacement formula to obtain an inverse transformation formula of Arnold replacement, and the original image is directly formed through the inverse transformation formula, wherein the inverse transformation formula of Arnold transformation is as follows:
6. the ENC electronic nautical chart zero-watermarking method based on the water depth feature of claim 2, wherein: in the step five of zero watermark extraction and inspection, whether the watermark data has copyright authentication is judged by comparing the similarity value with a set threshold value, and the calculation formula of the similarity (NC) is as follows:
wherein W (i, j) represents the pixel value at (i, j) in the original watermark data, W' (i, j) represents the pixel value at (i, j) in the watermark data extracted from the vector chart, m, n represents the values of the row and column of the watermark picture data,
when NC is 1, the extracted watermark picture data is completely the same as the original watermark picture data, and the picture is not changed after being attacked; when the NC value is between 0 and 1, the closer to 1, the higher the data similarity is, and the watermark robustness is strong; and conversely, the lower the similarity is, the lower the watermark robustness is, wherein the NC value is 0.7 as the threshold value for identifying the watermark.
7. The ENC electronic nautical chart zero-watermarking method based on the water depth feature of claim 2, wherein: in the step five of zero watermark extraction and inspection, the comparison and verification are measured by the structural similarity SSIM, and the SSIM is as follows:
SSIM(W,W')＝l(W,W')c(W,W')s(W,W')#(4)
where W is the watermark image, W' is the extracted watermark image,
the closer the value of SSIM is to 1, the more similar the two images are and the better the quality of the images is.
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