Source: http://www.google.com/patents/US6442284?dq=5,884,271
Timestamp: 2015-01-30 14:42:59
Document Index: 124966978

Matched Legal Cases: ['Application No. 60', 'application No. 09', 'application No. 09', 'application No. 09', 'application No. 09', 'application No. 60']

Patent US6442284 - Watermark detection utilizing regions with higher probability of success - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsThe 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...http://www.google.com/patents/US6442284?utm_source=gb-gplus-sharePatent US6442284 - Watermark detection utilizing regions with higher probability of successAdvanced Patent SearchPublication numberUS6442284 B1Publication typeGrantApplication numberUS 09/302,663Publication dateAug 27, 2002Filing dateApr 30, 1999Priority dateMar 19, 1999Fee statusPaidPublication number09302663, 302663, US 6442284 B1, US 6442284B1, US-B1-6442284, US6442284 B1, US6442284B1InventorsAmmon Gustafson, Geoffrey Rhoads, Adnan V. Alattar, Ravi K. Sharma, Clay DavidsonOriginal AssigneeDigimarc CorporationExport CitationBiBTeX, EndNote, RefManPatent Citations (7), Non-Patent Citations (7), Referenced by (60), Classifications (5), Legal Events (9) External Links: USPTO, USPTO Assignment, EspacenetWatermark detection utilizing regions with higher probability of successUS 6442284 B1Abstract 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.
NPI=Abs Value(4�Intensity−(sum of intensities of pixels above, below, right and left)), where �Abs Value� means �take Absolute value of,� and
NPI=Abs Value(4�Intensity−(sum of intensities of pixels above, below, right and left)), where �Abs Value� means �take Absolute value of;�
where T1 is a �threshold� with a value selected to be near the average value of NPI. 5. A system for determining the probability of finding a watermark in a region of an image including:
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. 8. 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:
where T1 is a �threshold� with a value selected to be near the average value of NPI. 9. A method of detecting digital watermarks in an image by:
RELATED APPLICATION This application claims the benefit of U.S. Provisional Application No. 60/125,349, filed Mar. 19, 1999.
FILED OF THE INVENTION The present invention relates to steganography and more particularly to the detection of digital watermarks in images.
BACKGROUND OF THE INVENTION The technology for embedding digital watermarks in images is well known. Likewise, the technology for detecting and reading the data payload carried by digital watermarks is well known. Commercial systems are available for performing such operations.
SUMMARY OF THE INVENTION 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 examined. For example a region that is entirely white or entirely black has zero variance. Such a region can not carry watermark data, hence regions with zero or low variance can be eliminated from further processing. Furthermore, if 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 edges between areas of different luminance which are spread over the entire region. The regions with the high variance and with edginess that is spread widely in the region are selected for further processing to detect watermark data.
BRIEF DESCRIPTION OF THE FIGURE FIG. 1 shows an image with different regions.
DETAILED DESCRIPTION OF AN EMBODIMENTS OF THE INVENTION Digital watermarks are generally inserted into images in a redundant manner. That is, images are divided into regions and the same data is inserted into each region of the image. The ability of a particular region of an image to effectively carry digital watermark data, depends upon the characteristics of the image in the particular region. Different areas in an image may have more or less ability to carry watermark data. For example an area in an image that is entirely white or entirely black will not have the ability to carry watermark data without changing the appearance of the area. Modern watermarking programs use perceptually adaptive techniques when inserting watermark data into an image. The amount of watermark energy inserted into a region is adjusted depending on the characteristics of the region so as to avoid changing the visual appearance of the image. For example, no watermark energy would be applied to an area of an image that is entirely white or entirely black.
While there is a low probability that areas with a low variation in luminance contain watermark data, there is also a low probability that certain areas which have a high variance in luminance contain watermark data. For example, the area in row c column 6 contains the border between black area 11 and the remainder of the image. In areas such as the area at row c column 6, the variance in luminance would be high due to the edge effect; however, the high variance in luminance in an area such as row c column 6 would not indicate a high probability of finding watermark data. In a region such as row c column 6 the �edginess spread� is low. If a region has a low �edginess spread�, the probability of finding watermark data is relatively low.
Thus, after the regions with high luminance variation values are found, those regions are tested to determine �edginess spread�. That is, to locate regions where the variance is concentrated along a division between regions each of which have a low variance. Regions where variance in luminance is concentrated along a division between regions each of which have a low variance in luminance are said to have a low edginess spread.
NPI=Abs Value (4�Intensity−(sum of intensities of pixels above, below, right and left)) where �Abs Value� means �take Absolute value of�
where T1 is a �threshold� with a value selected to be near the average value of NPI
The above calculation gives a second value (ES or edginess spread) for each region. The luminance variance value and the edginess spread value are then combined to give a �probability index� which indicates the probability of finding a watermark in a particular region.
ES=(Sum of NPI for all pixels that exceed T 1/total number of pixels) By testing the success obtained with different groups of images of interest which have different characteristics one can determine which equation gives the best results for images with a particular set of characteristics.
It is noted that patent application Ser. No. 09/074,034 filed May 6, 1998 entitled: �Methods and Systems for Watermark Processing of Line Art Images� describes a technique for inserting watermarks into a lined image by varying the width of the lines to indicate watermark data. The present invention would still produce satisfactory results with watermarks of the type described in the above referenced application. The reason is that the line widths in a typical image which uses the technique described in the above application have a width significantly smaller than the size of a pixel in an image from a typical 300 or 600 DPI scanner. The edginess measurement detected by the present invention relates to edges between regions, each of which are wider than a single pixel.
Filtered intensity=Old intensity−average intensity of the 8 neighbors of the pixel The second step consists of applying a nonlinear operator (e.g., a signum operator etc.) to the filtered output of the high pass or edge detection filter. The filtered intensity (FI) of each pixel calculated as given above is modified as follows: New   Intensity = a   if   ( FI > TI ) = b   if   ( T2 <= FI <= T1 ) = c   if   ( F1 < T2 ) Where: a, b, and c are values, and T1 and T2 are thresholds selected to implement a specific nonlinear operator.
Since some watermarking programs redundantly embed �pay-load� or watermark data in multiple blocks in an image, in order to further enhance the ability to detect the watermark data from such programs the following technique can be used. Following the non-linear filtering operation, the power spectrum of several blocks can be added together. Due to the redundant embedding, the watermark frequencies repeat through several blocks, the power at those frequencies adds up if the power spectrum of several blocks are added together. The image frequencies from block to block are generally non-repetitive and hence they get averaged out when the power spectrum of several blocks are added together. The power spectrum that results from adding together the power spectrum from several blocks contains a higher signal-to-noise ratio watermark signal. The power spectrum can then be more easily correlated with the power spectrum of the watermark.
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KgVisible authentication patterns for printed documentWO2004035321A1 *Oct 14, 2003Apr 29, 2004Digimarc CorpIdentification document and related methods* Cited by examinerClassifications U.S. Classification382/100, 713/176International ClassificationG06T1/00Cooperative ClassificationG06T1/0078European ClassificationG06T1/00W6TLegal EventsDateCodeEventDescriptionJan 28, 2014FPAYFee paymentYear of fee payment: 12Nov 2, 2010ASAssignmentOwner name: DIGIMARC CORPORATION, OREGONFree format text: MERGER;ASSIGNOR:DMRC CORPORATION;REEL/FRAME:025227/0832Effective date: 20080903Effective date: 20080801Free format text: MERGER;ASSIGNOR:DMRC LLC;REEL/FRAME:025227/0808Owner name: DMRC CORPORATION, OREGONOct 29, 2010ASAssignmentOwner name: DMRC LLC, OREGONFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:DIGIMARC CORPORATION (A DELAWARE CORPORATION);REEL/FRAME:025217/0508Effective date: 20080801Sep 14, 2010ASAssignmentOwner name: DIGIMARC CORPORATION (A DELAWARE CORPORATION), OREFree format text: MERGER;ASSIGNOR:DIGIMARC CORPORATION (AN OREGON CORPORATION);REEL/FRAME:024982/0707Effective date: 19991124May 12, 2010ASAssignmentOwner name: DIGIMARC CORPORATION (AN OREGON CORPORATION),OREGOFree format text: MERGER;ASSIGNOR:DIGIMARC CORPORATION (A DELAWARE CORPORATION);US-ASSIGNMENT DATABASE UPDATED:20100512;REEL/FRAME:24369/582Effective date: 20100430Free format text: MERGER;ASSIGNOR:DIGIMARC CORPORATION (A DELAWARE CORPORATION);US-ASSIGNMENT DATABASE UPDATED:20100513;REEL/FRAME:24369/582Free format text: MERGER;ASSIGNOR:DIGIMARC CORPORATION (A DELAWARE CORPORATION);US-ASSIGNMENT DATABASE UPDATED:20100518;REEL/FRAME:24369/582Free format text: MERGER;ASSIGNOR:DIGIMARC CORPORATION (A DELAWARE CORPORATION);US-ASSIGNMENT DATABASE UPDATED:20100525;REEL/FRAME:24369/582Free format text: MERGER;ASSIGNOR:DIGIMARC CORPORATION (A DELAWARE CORPORATION);REEL/FRAME:24369/582Free format text: MERGER;ASSIGNOR:DIGIMARC CORPORATION (A DELAWARE CORPORATION);REEL/FRAME:024369/0582Owner name: DIGIMARC CORPORATION (AN OREGON CORPORATION), OREGJan 22, 2010FPAYFee paymentYear of fee payment: 8Nov 5, 2008ASAssignmentOwner name: DIGIMARC CORPORATION (FORMERLY DMRC CORPORATION),Free format text: CONFIRMATION OF TRANSFER OF UNITED STATES PATENT RIGHTS;ASSIGNOR:L-1 SECURE CREDENTIALING, INC. 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