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Ame S-912 Image Grabber Driver

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AME S-912 IMAGE GRABBER DRIVERS FOR WINDOWS 7

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Ame S-912 Image Grabber Driver

For example, the access controller 1 10 may implement one or more image recognition algorithms, such as a facial recognition algorithm, a target recognition algorithm, a feature identification algorithm, etc. In some examples, if Ame S-912 Image Grabber access controller determines that the video sequence depicts a particular e.

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In some examples, Ame S-912 Image Grabber access controller 1 10 then permits the subject to access the system, area, etc. However, if the access controller is unable to authenticate the subject using the video sequence, in some examples the access controller indicates that authentication of the subject was unsuccessful and prevents the subject from accessing the system, area, etc.

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For example, the visual authentication verifier can be employed in any environment of use in which determining Ame S-912 Image Grabber a captured video sequence depicts a scene including content generated by a video display of a media device would be beneficial. In the illustrated example of FIGS. For example, the camera may be positioned to capture an area in front of a doorway subject to access control, an area in front of a computer terminal, etc.

Because the video sequence captured by the camera is of a real subject, the example visual authentication verifier of the video-based authentication system does not detect any regions of fluctuating pixels in a sequence of input images obtained from the video sequence captured by the Ame S-912 Image Grabber Because the video sequence captured by the camera depicts content generated by a video display, the example visual authentication verifier of the video-based authentication system detects one or more regions of fluctuating pixels in the sequence of input images obtained from the video sequence captured by the camera The example image capturer of FIG.

Ame S-912 Image Grabber the illustrated example, the second sequence of input images is the sequence of input images to be used by the visual authentication verifier to determine whether the video captured by the camera is valid or is associated with a spoofing attack. For example, the second e. In such examples, the image grabber captures the first sequence of input images from the camera video output at a first e. For example, if the second e. The image selector of the illustrated then downsamples e.

In some examples, the image selector utilizes a random number generator Ame S-912 Image Grabber select one input image from a respective group of input images.

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In Ame S-912 Image Grabber examples, the image selector utilizes a pre-defined selection pattern, a round-robin technique, etc. The example fluctuating pixel detector of FIG. In the illustrated example, the candidate region identifier processes successive pairs of difference images in the sequence of difference images to identify fluctuating pixels. For example, the candidate region identifier may determine that a pixel is a fluctuating pixel if 1 a first difference image indicates that the value e.

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The second threshold amount may be the same or different from e. If the candidate region identifier determines that the value of an examined pixel location has returned to be within the second threshold amount, then the candidate region identifier determines that pixel at the examined location fluctuated Ame S-912 Image Grabber at least two values e.

Then, the candidate region identifier determines the number of pixels included in each group of neighboring fluctuating pixels. In the illustrated example, the fluctuation evaluator compares the respective numbers of pixels included in the groups of neighboring fluctuating pixels to a threshold number e. If any of the groups of neighboring fluctuating pixels contains a number of pixels that satisfies e.

Additionally, in some examples, the fluctuation evaluator identifies the region s of Ame S-912 Image Grabber pixels as corresponding to the location s of the group s of neighboring fluctuating pixels satisfying the threshold number of pixels. Assuming the example fluctuation evaluator of the fluctuating pixel detector determines that the number of pixels included in the example region 1 satisfies the threshold number described above, the region 1 is identified as a fluctuating pixel region.

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Further still, the example video-based authentication system of FIGS. Further, although the example program s is are described with reference to the flowcharts illustrated in FIGS.

For example, with reference to the flowcharts illustrated in FIGS. Ame S-912 Image Grabber used herein, "tangible computer readable storage medium" and "tangible machine readable storage medium" are used interchangeably. Additionally or alternatively, the example processes of FIGS.

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As used herein, when the phrase "at least" is used as the transition term in a preamble of a claim, it is open-ended in the same manner as the term "comprising" is open ended. Also, as used herein, the terms "computer readable" and "machine readable" are considered equivalent unless indicated otherwise. The example program may be executed when the example video-based authentication Ame S-912 Image Grabber is activated e.

With reference to the preceding figures and associated written descriptions, the example program of FIG. An example program that may be used to implement the processing at block is illustrated in FIG.

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