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11.发明授权公开(公告)号：US09891883B2
公开(公告)日：2018-02-13
申请号：US15192925
申请日：2016-06-24
Applicant: Digimarc Corporation
Inventor： Ravi K. Sharma , Shankar Thagadur Shivappa , Osama M. Alattar , Brett A. Bradley , Scott M. Long , Ajith M. Kamath , Vojtech Holub , Hugh L. Brunk , Robert G. Lyons , Aparna R. Gurijala
CPC classification number: G06F3/165 , G10L19/018 , G10L19/0212 , G10L25/09 , G10L25/21
Abstract: Methods and arrangements involving electronic devices, such as smartphones, tablet computers, wearable devices, etc., are disclosed. One arrangement involves a low-power processing technique for discerning cues from audio input. Another involves a technique for detecting audio activity based on the Kullback-Liebler divergence (KLD) (or a modified version thereof) of the audio input. Still other arrangements concern techniques for managing the manner in which policies are embodied on an electronic device. Others relate to distributed computing techniques. A great variety of other features are also detailed.
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12.发明授权公开(公告)号：US12014441B2
公开(公告)日：2024-06-18
申请号：US17479910
申请日：2021-09-20
Applicant: Digimarc Corporation
Inventor： Ravi K. Sharma , John D. Lord , Robert G. Lyons , Osama M. Alattar , Jacob L Boles
CPC classification number: G06T1/0064 , G06T3/02 , G06T3/10 , G06T2201/0052 , G06T2201/0065 , G06T2201/0081
Abstract: Signal processing devices and methods estimate a geometric transform of an image. One method measures correlation between a transformed reference signal component and an image, updates, based on the measured correlation that is below a threshold, coordinates of the reference signal component to a location within a neighborhood around the coordinates of the transformed reference signal component; determines a new geometric transform that transforms the reference signal components to updated coordinates; and applies the new geometric transform to extract encoded digital data from the image.
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公开(公告)号：US20220331841A1
公开(公告)日：2022-10-20
申请号：US17721694
申请日：2022-04-15
Applicant: Digimarc Corporation
Inventor： Tomas Filler , Vojtech Holub , Ravi K. Sharma , Tony F. Rodriguez , Osama M. Alattar , Adnan M. Alattar , Hugh L. Brunk , Brett A. Bradley , Ajith M. Kamath
Abstract: A waste stream is analyzed and sorted to segregate different items for recycling. Certain features of the technology improve the accuracy with which waste stream items are diverted to collection repositories. Other features concern adaptation of neural networks in accordance with context information sensed from the waste. Still other features serve to automate and simplify maintenance of machine vision systems used in waste sorting. Yet other aspects of the technology concern marking 2D machine readable code data on items having complex surfaces (e.g., food containers with integral ribbing for structural strength or juice pooling), to mitigate issues that such surfaces can introduce in code reading. Still other aspects of the technology concern prioritizing certain blocks of conveyor belt imagery for analysis. Yet other aspects of the technology concern joint use of near infrared spectroscopy, artificial intelligence, digital watermarking, and/or other techniques, for waste sorting. A variety of further features and arrangements are also detailed.
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公开(公告)号：US20220055071A1
公开(公告)日：2022-02-24
申请号：US17470674
申请日：2021-09-09
Applicant: Digimarc Corporation
Inventor： Ravi K. Sharma , Tomas Filler , Vojtech Holub , Osama M. Alattar , Hugh L. Brunk , John D. Lord , Geoffrey B. Rhoads , William Y. Conwell , Ajith M. Kamath
Abstract: A plastic item, such as a beverage bottle, can convey two distinct digital watermarks, encoded using two distinct signaling protocols. A first, printed label watermark conveys a retailing payload, including a Global Trade Item Number (GTIN) used by a point-of-sale scanner in a retail store to identify and price the item when presented for checkout. A second, plastic texture watermark may convey a recycling payload, including data identifying the composition of the plastic. The use of two different signaling protocols assures that a point-of-sale scanner will not spend its limited time and computational resources working to decode the recycling watermark, which may lack data needed for retail checkout. In some embodiments, a recycling apparatus makes advantageous use of both types of watermarks to identify the plastic composition of the item (e.g., relating GTIN to plastic type using an associated database), thereby increasing the fraction of items that are correctly identified for sorting and recycling. In other embodiments the plastic item (or a label thereon) bears only a single watermark. A great number of other features and arrangements are also detailed.
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公开(公告)号：US20210352192A1
公开(公告)日：2021-11-11
申请号：US17371964
申请日：2021-07-09
Applicant: Digimarc Corporation
Inventor： Ravi K. Sharma , Tomas Filler , Vojtech Holub , Osama M. Alattar , Hugh L. Brunk , John D. Lord , William Y. Conwell
IPC: H04N5/225 , G06F21/16 , H04N21/44 , H04N21/2389 , H04N21/8358 , G09C5/00
Abstract: A plastic item, such as a beverage bottle, conveys two distinct digital watermarks, encoded using two distinct signaling protocols. A first, printed label watermark conveys a retailing payload, including a Global Trade Item Number (GTIN) used by a point-of-sale scanner in a retail store to identify and price the item when presented for checkout. A second, plastic texture watermark conveys a recycling payload, including data identifying the composition of the plastic. The use of two different signaling protocols assures that a point-of-sale scanner will not spend its limited time and computational resources working to decode the recycling watermark, which lacks the data needed for retail checkout. In some embodiments, a recycling apparatus makes advantageous use of both types of watermarks to identify the plastic composition of the item (e.g., relating GTIN to plastic type using an associated database), thereby increasing the fraction of items that are correctly identified for sorting and recycling. A great number of other features and arrangements are also detailed.
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Patent Agency Ranking
公开(公告)号：US10607311B2
公开(公告)日：2020-03-31
申请号：US15899292
申请日：2018-02-19
Applicant: Digimarc Corporation
Inventor： Osama M. Alattar , Adnan M. Alattar
Abstract: The present invention relates generally to digital watermarking. One aspect of the disclosure includes a method comprising: obtaining data representing imagery; using one or more configured processors, analyzing a plurality of portions of the data to detect a redundantly embedded watermark signal, the analyzing producing detection statistics for each of the plurality of portions, the detection statistics comprising a payload signature, a rotation angle and a scale factor for each portion of the plurality of portions; accumulating payload signatures based on compatible rotation angles and scale factors, said accumulating yielding an accumulated payload signature; and decoding a plural-bit payload from the accumulated payload signature. Of course, many other aspects and disclosure are provided in this patent document.
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17.发明申请公开(公告)号：US20180330464A1
公开(公告)日：2018-11-15
申请号：US15967214
申请日：2018-04-30
Applicant: Digimarc Corporation
Inventor： Ravi K. Sharma , John D. Lord , Robert G. Lyons , Osama M. Alattar , Jacob L. Boles
CPC classification number: G06T1/0064 , G06K9/6206 , G06T3/0006 , G06T3/0056 , G06T2201/0052 , G06T2201/0065 , G06T2201/0081
Abstract: Signal processing devices and methods estimate a geometric transform of an image signal. From a seed set of transform candidates, a direct least squares method applies a seed transform candidate to a reference signal and then measures correlation between the transformed reference signal and an image signal in which the reference signal is encoded. Geometric transform candidates encompass differential scale and shear, which are useful in approximating a perspective transform. For each candidate, update coordinates of reference signal features are identified in the image signal and provided as input to a least squares method to compute an update to the transform candidate. The method iterates so long as the update of the transform provides a better correlation. At the end of the process, the method identifies a geometric transform or set of top transforms based on a further analysis of correlation, as well as other results. Phase characteristics are exploited in the process of updating coordinates and measuring correlation. The geometric transform is used as an approximation of the geometric distortion of an image after digital data is encoded in it, and is used to compensate for this distortion to facilitate extracting embedded digital messages from the image. Due to the errors in the approximation, a signal confidence metric is determined and used to weight message symbol estimates extracted from the image.
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公开(公告)号：US20180276782A1
公开(公告)日：2018-09-27
申请号：US15899292
申请日：2018-02-19
Applicant: Digimarc Corporation
Inventor： Osama M. Alattar , Adnan M. Alattar
CPC classification number: G06T1/005 , G06K9/00744 , G06T2201/0051 , G06T2201/0061 , G06T2201/0065 , H04N1/32203 , H04N1/32267 , H04N1/32288 , H04N1/32352
Abstract: The present invention relates generally to digital watermarking. One aspect of the disclosure includes a method comprising: obtaining data representing imagery; using one or more configured processors, analyzing a plurality of portions of the data to detect a redundantly embedded watermark signal, the analyzing producing detection statistics for each of the plurality of portions, the detection statistics comprising a payload signature, a rotation angle and a scale factor for each portion of the plurality of portions; accumulating payload signatures based on compatible rotation angles and scale factors, said accumulating yielding an accumulated payload signature; and decoding a plural-bit payload from the accumulated payload signature. Of course, many other aspects and disclosure are provided in this patent document.
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公开(公告)号：US20230325960A1
公开(公告)日：2023-10-12
申请号：US18181502
申请日：2023-03-09
Applicant: Digimarc Corporation
Inventor： Tony F. Rodriguez , Osama M. Alattar , Hugh L. Brunk , Joel R. Meyer , William Y. Conwell , Ajith M. Kamath
IPC: G06T1/00 , G06F21/16 , G06V10/24 , G06V20/20 , G06F18/214 , G06F18/2413 , G06V10/774
CPC classification number: G06T1/0021 , G06F21/16 , G06V10/245 , G06V20/20 , G06F18/214 , G06F18/2155 , G06F18/2413 , G06V10/774 , G06V10/7753
Abstract: A sequence of images depicting an object is captured, e.g., by a camera at a point-of-sale terminal in a retail store. The object is identified, such as by a barcode or watermark that is detected from one or more of the images. Once the object's identity is known, such information is used in training a classifier (e.g., a machine learning system) to recognize the object from others of the captured images, including images that may be degraded by blur, inferior lighting, etc. In another arrangement, such degraded images are processed to identify feature points useful in fingerprint-based identification of the object. Feature points extracted from such degraded imagery aid in fingerprint-based recognition of objects under real life circumstances, as contrasted with feature points extracted from pristine imagery (e.g., digital files containing label artwork for such objects). A great variety of other features and arrangements—some involving designing classifiers so as to combat classifier copying—are also detailed.
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公开(公告)号：US20210217128A1
公开(公告)日：2021-07-15
申请号：US17152498
申请日：2021-01-19
Applicant: Digimarc Corporation
Inventor： Tony F. Rodriguez , Osama M. Alattar , Hugh L. Brunk , Joel R. Meyer , William Y. Conwell , Ajith M. Kamath
Abstract: A sequence of images depicting an object is captured, e.g., by a camera at a point-of-sale terminal in a retail store. The object is identified, such as by a barcode or watermark that is detected from one or more of the images. Once the object's identity is known, such information is used in training a classifier (e.g., a machine learning system) to recognize the object from others of the captured images, including images that may be degraded by blur, inferior lighting, etc. In another arrangement, such degraded images are processed to identify feature points useful in fingerprint-based identification of the object. Feature points extracted from such degraded imagery aid in fingerprint-based recognition of objects under real life circumstances, as contrasted with feature points extracted from pristine imagery (e.g., digital files containing label artwork for such objects). A great variety of other features and arrangements—some involving designing classifiers so as to combat classifier copying—are also detailed.
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