US6442284B1
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Watermark detection utilizing regions with higher probability of success
Assignee: Digimarc Corp
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Filing: 1999-04-30
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Granted: 2002-08-27
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Expires: 2019-04-30
Abstract
Abstract The present invention detects the presence of a watermark in-an image by using a multi-step process. First, the image is examined to determine which regions of the image have characteristics such that there is a high probability that a watermark signal can be detected in that region of the image. Next the regions that have a high probability that a watermark can be detected (in contrast to all regions of the image) are examined to find watermark data. In order to determine the probability of finding watermark data in a particular region of an image, the amount of "variance" in the intensity of the pixels in the region is first examined. For example a region that is entirely white or entirely black has zero variance in luminance. Such a region can not carry watermark data, hence regions with zero or low variance can be eliminated from further processing. Furthermore, if a high variance in a region is a result of the fact that the region has an abrupt border or edge between two highly contrasting regions, the high variance does not indicate a high probability that a watermark signal will be detected in the region. Therefore, after regions with high variance are located, these regions are next examined to look for regions with high edginess spread. Finally, regions with the high variance and high edginess spread are selected for further processing to detect watermark data. For those regions selected for further processing, the detection process can be enhanced by filtering the data with a two step process to increase the signal to noise ratio of the watermark signal. First a high pass filter (e.g. a Laplacian operator) is applied to each region. This filtering operation in effect established a new intensity value for each pixel in the region. Next a nonlinear operator (e.g. a signum function) is applied to the output from the first filter operation. The resulting data is examined to detect watermark data.
Inventors
- 👤 Ammon Gustafson
- 👤 Geoffrey Rhoads
- 👤 Adnan V. Alattar
- 👤 Ravi K. Sharma
- 👤 Clay Davidson
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 19:25
CPC Classifications
G; G06; G06T; G06T1/00; G06T1/0021; G06T1/005; G06T1/0078
Claims Analysis
Total Claims: 27
Claim 1
Independent Claim
37 words
A method for determining the probability of finding a watermark in a region of an image including the steps of: determining a variance in the luminance of the region, and determining an edginess spread of the region.
Claim 2
Independent Claim
37 words
A method for determining the probability of finding a watermark in a region of an image including the steps of: determining a variance in the luminance of the region, and determining an edginess spread of the region.
Claim 3
Dependent Claim
27 words
The method recited in claim 1 where the variance in the luminance of a region is determined by calculating: Variance=sum((intensity) 2 /number of pixels)−mean intensity 2 .
Claim 4
Dependent Claim
63 words
The method recited in claim 1 where the edginess spread of the region is determined by calculating a NPI (New Pixel Intensity) value and edginess spread (ES) value as follows: NPI=Abs Value(4×Intensity−(sum of intensities of pixels above, below, right and left)), where “Abs Value” means “take Absolute value of,” and ES=(Sum of NPI for all pixels that exceed a threshold)/total number of pixels.
Claim 5
Dependent Claim
136 words
The method recited in claim 1 where the edginess spread of the region is determined by calculating a NPI (New Pixel Intensity) value and edginess spread (ES) value as follows: NPI=Abs Value(4×Intensity−(sum of intensities of pixels above, below, right and left)), where “Abs Value” means “take Absolute value of;” Calculate an NNPI value for each pixel as follows: NNPI = 1 if NPI exceeds a T1 , and = 0 if NPI is less than or equal to T1 ; and ES=(Sum of NNPI for all pixels)/total number of pixels, where T 1 is a “threshold” with a value selected to be near the average value of NPI.
Claim 6
Independent Claim
38 words
A system for determining the probability of finding a watermark in a region of an image including: means for determining a variance in the luminance of the region, and means for determining an edginess spread of the region.
Claim 7
Independent Claim
38 words
A system for determining the probability of finding a watermark in a region of an image including: means for determining a variance in the luminance of the region, and means for determining an edginess spread of the region.
Claim 8
Dependent Claim
29 words
The system recited in claim 5 where the variance in the luminance of a region is determined by means for calculating: Variance=sum((intensity) 2 /number of pixels)−mean intensity 2 .
Claim 9
Dependent Claim
67 words
The system recited in claim 5 where the edginess spread of the region is determined by means for calculating a new pixel intensity value NPI) and an edginess spread (ES) value as follows: NPI=Abs Value(4×Intensity−(sum of intensities of pixels above, below, right and left)), where “Abs Value” means “take the Absolute value of,” and ES=(Sum of NPI for all pixels that exceed a threshold)/total number of pixels.
Claim 10
Dependent Claim
137 words
The system recited in claim 5 where the edginess of the region is determined by means for calculating new pixel intensity value (NPI) and an edginess spread (ES) value as follows: NPI=Abs Value(4×Intensity−(sum of intensities of pixels above, below, right and left)), where “Abs Value” means “take Absolute value of;” Calculate an NNPI value for each pixel as follows: NNPI = 1 if NPI exceeds a T1 , and = 0 if NPI is less than or equal to T1 ; and ES=(Sum of NNPI for all pixels)/total number of pixels, where T 1 is a “threshold” with a value selected to be near the average value of NPI.
Claim 11
Independent Claim
98 words
A method of detecting digital watermarks in an image by: first, determining the probability that watermark data is located in various regions of the image, and second, processing the regions of the image with the highest probability before processing regions with low probability in order to locate watermark data, wherein the step of determining the probability that watermark data is located in various regions of the image is performed by first calculating the variance in the luminance of the pixels in the region and by determining the edginess spread of regions which have a high variation in luminance.
Claim 12
Independent Claim
98 words
A method of detecting digital watermarks in an image by: first, determining the probability that watermark data is located in various regions of the image, and second, processing the regions of the image with the highest probability before processing regions with low probability in order to locate watermark data, wherein the step of determining the probability that watermark data is located in various regions of the image is performed by first calculating the variance in the luminance of the pixels in the region and by determining the edginess spread of regions which have a high variation in luminance.
Claim 13
Independent Claim
100 words
A system for detecting digital watermarks in an image including means for determining the probability that watermark data is located in various regions of the image, and means for processing the regions of the image with the highest probability before processing regions with lower probability in order to locate watermark data, wherein the means for determining the probability that watermark data is located in various regions of the image includes means for calculating e variance in the luminance of the pixels in the region and means For determining the edginess spread of regions which have a high variation in luminance.
Claim 14
Independent Claim
100 words
A system for detecting digital watermarks in an image including means for determining the probability that watermark data is located in various regions of the image, and means for processing the regions of the image with the highest probability before processing regions with lower probability in order to locate watermark data, wherein the means for determining the probability that watermark data is located in various regions of the image includes means for calculating e variance in the luminance of the pixels in the region and means For determining the edginess spread of regions which have a high variation in luminance.
Claim 15
Independent Claim
98 words
A method of detecting watermark data in an image which can be divided into blocks of pixels, comprising the steps of; detecting blocks which have a high probability of containing watermark data to select a high probability group of blocks, and filtering the high probability group of blocks which have a high probability of containing watermark data using a process comprising: first computing a new intensity value for each pixel in each high probability block using a high pass filter, and next computing a second new intensity value by applying a non-linear function to the new intensity value.
Claim 16
Independent Claim
98 words
A method of detecting watermark data in an image which can be divided into blocks of pixels, comprising the steps of; detecting blocks which have a high probability of containing watermark data to select a high probability group of blocks, and filtering the high probability group of blocks which have a high probability of containing watermark data using a process comprising: first computing a new intensity value for each pixel in each high probability block using a high pass filter, and next computing a second new intensity value by applying a non-linear function to the new intensity value.
Claim 17
Dependent Claim
35 words
The method recited in claim 11 wherein the first computing a new intensity value step computes the new intensity value using the following equation: New intensity=Old intensity−average intensity of the 8 neighbors of the pixel.
Claim 18
Dependent Claim
73 words
The method recited in claim 11 wherein the second new intensity value is calculated as follows: Second New intensity = 1 if ( Filtered intensity > 0 ) ; = 0 if ( Filtered intensity = 0 ) ; and = - 1 if ( Filtered intensity < 0 ) .
Claim 19
Independent Claim
104 words
A system for detecting watermark data in an image which call be divided into blocks of pixels, comprising the steps of: means for detecting blocks which have a high probability of containing watermark data to select a high probability group of blocks, and means for filtering the high probability group of blocks which have a high probability of containing watermark data, said filtering means comprising: means for first computing a new intensity value for each pixel in each high probability block using a Laplacian operator, and means for computing a second new intensity value by applying a signum function to the new intensity value.
Claim 20
Independent Claim
104 words
A system for detecting watermark data in an image which call be divided into blocks of pixels, comprising the steps of: means for detecting blocks which have a high probability of containing watermark data to select a high probability group of blocks, and means for filtering the high probability group of blocks which have a high probability of containing watermark data, said filtering means comprising: means for first computing a new intensity value for each pixel in each high probability block using a Laplacian operator, and means for computing a second new intensity value by applying a signum function to the new intensity value.
Claim 21
Dependent Claim
30 words
The system recited in claim 14 wherein the Laplacian operator computes the new intensity value using the following equation: New intensity=Old intensity−average intensity of the 8 neighbors of the pixel.
Claim 22
Dependent Claim
73 words
The system recited in claim 14 wherein the second new intensity value is calculated as follows: Second New intensity = 1 if ( Filtered intensity > 0 ) ; = 0 if ( Filtered intensity = 0 ) ; and = - 1 if ( Filtered intensity < 0 ) .
Claim 23
Independent Claim
75 words
A method of detecting watermark data in a group of pixels including the steps of: first computing a new intensity value (NIV) for each pixel in the group of pixels using a high pass filter, and next computing a second new intensity value by applying a non linear operator to the NIV values, the second new intensity values collectively comprising a set, and processing the set of second new intensity values to detect a watermark.
Claim 24
Independent Claim
75 words
A method of detecting watermark data in a group of pixels including the steps of: first computing a new intensity value (NIV) for each pixel in the group of pixels using a high pass filter, and next computing a second new intensity value by applying a non linear operator to the NIV values, the second new intensity values collectively comprising a set, and processing the set of second new intensity values to detect a watermark.
Claim 25
Dependent Claim
30 words
The method recited in claim 17 wherein the high pass filter computes the new intensity value using the following equation: NIV=Old intensity−average intensity of the 8 neighbors of the pixel.
Claim 26
Dependent Claim
73 words
The method recited in claim 17 wherein the second new intensity value is calculated as follows: Second New intensity = 1 if ( Filtered intensity > 0 ) ; = 0 if ( Filtered intensity = 0 ) ; and = - 1 if ( Filtered intensity < 0 ) .
Claim 27
Dependent Claim
80 words
The method recited in claim 17 wherein the second new intensity value (SNI) is calculated by a non-linear operator as follows: SNI = a if ( NIV > T1 ) ; = b if ( T2 <= NIV <= T1 ) ; and = c if ( NIV < T2 ) , where: a, b, and c are selected values, and T 1 and T 2 are thresholds.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
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| 3.5 Years (Year 4) | 2005-08-26 | 2006-02-25 | 2006-08-27 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2009-08-26 | 2010-02-25 | 2010-08-27 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2013-08-26 | 2014-02-25 | 2014-08-27 | $7700.00 | Window Closed / Lapsed |