Robust recognizer of perceptually similar content
First Claim
1. A method for hashing a digital signal, the method comprising:
- transforming a digital signal into a digital signal transform;
quantizing the digital signal transform;
geometric-region-growing the digital signal transform;
generating a recognition value of the digital signal.
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Abstract
An implementation of a technology is described herein for recognizing the perceptual similarity of the content of digital goods. At least one implementation, described herein, introduces a new hashing technique. More particularly, this hashing technique produces hash values for digital goods that are proximally near each other, when the digital goods contain perceptually similar content. In other words, if the content of digital goods are perceptually similar, then their hash values are, likewise, similar. The hash values are proximally near each other. This is unlike conventional hashing techniques where the hash values of goods with perceptually similar content are far apart with high probability in some distance sense (e.g., Hamming). This abstract itself is not intended to limit the scope of this patent. The scope of the present invention is pointed out in the appending claims.
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Citations
29 Claims
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1. A method for hashing a digital signal, the method comprising:
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transforming a digital signal into a digital signal transform;
quantizing the digital signal transform;
geometric-region-growing the digital signal transform;
generating a recognition value of the digital signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A method for hashing a digital signal, the method comprising:
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transforming a digital signal into a digital signal transform;
quantizing the digital signal transform;
self-correcting iterative filtering of the digital signal transform;
generating a recognition value of the digital signal. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21)
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22. A method for hashing a digital signal, the method comprising:
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pseudorandomly segmenting a digital signal into one or more segments;
for one or more of the segments;
transforming a segment into a segment transform;
quantizing the segment transform;
self-correcting iterative filtering of the segment transform;
combining one or more of the segments;
generating a recognition value of the digital signal. - View Dependent Claims (23, 24, 25)
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26. A system for digital signal similarity recognition, the system comprising:
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a transformer configured to transform a digital signal into a signal transform;
a quantizer configured to quantitize the signal transform;
a iterative geometric converter configured to convert the signal transform into a representation of the signal that emphasizes geometrically strong components of the signal while de-emphasizing geometrically weak components of the signal. - View Dependent Claims (27)
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28. A system for digital signal similarity recognition, the system comprising:
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a segmenter configured to pseudorandomly segment the digital signal into one or more of the segments;
a transformer configured to transform a segment into a segment transform;
a quantizer configured to quantitize the segment transform;
a iterative geometric converter configured to convert the segment transform into a representation of the segment that emphasizes geometrically strong components of the segment while de-emphasizing geometrically weak components of the segment;
a combiner configured to combine the output of the converter for one or more of the segments.
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29. One or more computer-readable media having computer-executable instructions that, when executed by a computer, performs the method comprising:
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transforming a digital signal into a digital signal transform;
quantizing the digital signal transform;
self-correcting iterative filtering of the digital signal transform;
generating a recognition value of the digital signal.
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Specification