WATERMARK SENSING METHODS AND ARRANGEMENTS

    公开(公告)号:US20210142514A1

    公开(公告)日:2021-05-13

    申请号:US16951308

    申请日:2020-11-18

    Abstract: The geometric pose of a patch of watermark data is estimated based on the position of a similar, but non-identical, patch of information within a data structure. The information in the data structure corresponds to a tiled array of calibration patterns that is sampled along at least three non-parallel paths. In a particular embodiment, the calibration patterns are sampled so that edges are globally-curved, yet locally-flat. Use of such information in the data structure enables enhanced pose estimation, e.g., speeding up operation, enabling pose estimation from smaller patches of watermark signals, and/or enabling pose estimation from weaker watermark signals. A great variety of other features and arrangements are also detailed.

    Hardware-adaptable watermark systems

    公开(公告)号:US10593008B2

    公开(公告)日:2020-03-17

    申请号:US16207509

    申请日:2018-12-03

    Abstract: There are many advantages to implementing a watermark-based system using dedicated hardware, rather than using software executing on a general purpose processor. These include higher speed and lower power consumption. However, hardware implementations incur substantial design and development costs. Moreover, because each watermarking application has its own design constraints and parameters, it has not been cost-effective to develop a hardware chip design for each, since such chips would typically not be manufactured in volumes sufficient to bring per-unit costs down to an acceptable level. The present technology provides various techniques for making watermarking hardware adaptable, so that a single chip can serve multiple diverse watermark applications. By so-doing, the advantages of hardware implementation are made available where it was formerly cost-prohibitive, thereby enhancing operation of a great variety of watermark-based systems.

    SENSING SYSTEMS
    65.
    发明申请
    SENSING SYSTEMS 审中-公开

    公开(公告)号:US20190213497A1

    公开(公告)日:2019-07-11

    申请号:US16247097

    申请日:2019-01-14

    Abstract: A system learns to automatically identify, and detect, contextual conditions that may serve as action triggers to help please a user (or avoid annoying a user). Among other features, a simple sensor arrangement is detailed which, in addition to producing a customary stream of high bandwidth sensor data, provides an output of low bandwidth data. This low-bandwidth data serves to identify a particular reference pattern with which the high-bandwidth sensor data is found to correspond. Such a sensor can employ reference patterns discovered through pseudo-random trials. A great number of other advantageous features and arrangements are also detailed.

    Signal Processors and Methods for Estimating Geometric Transformations of Images for Digital Data Extraction

    公开(公告)号:US20170193628A1

    公开(公告)日:2017-07-06

    申请号:US15211944

    申请日:2016-07-15

    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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