US6409085B1
Expired / Lapsed
US
⏱️ 0.0 years remaining
Method of recognizing produce items using checkout frequency
Assignee: NCR Voyix Corp
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Filing: 2000-08-16
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Granted: 2002-06-25
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Expires: 2020-08-16
Abstract
Abstract A method of recognizing produce items which uses checkout frequency as an a priori probability. The method includes the steps of collecting produce data from the produce item, determining DML values between the produce data and reference produce data for a plurality of types of produce items, determining conditional probability densities for all of the types of produce items using the DML values, combining the conditional probability densities together to form a combined conditional probability density, determining checkout frequencies for the produce types, determining probabilities for the types of produce items from the combined conditional probability density and the checkout frequencies, determining a number of candidate identifications from the probabilities, and identifying the produce item from the number candidate identifications.
Inventors
- 👤 Yeming Gu
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-10 02:04
CPC Classifications
G; G07; G07G; G07G1/00; G07G1/0036; G07G1/0045; G07G1/0054
Claims Analysis
Total Claims: 10
Claim 1
Independent Claim
118 words
A method of identifying a produce item comprising the steps of: (a) collecting produce data from the produce item; (b) determining DML values between the produce data and reference produce data for a plurality of types of produce items; (c) determining conditional probability densities for all of the types of produce items using the DML values; (d) combining the conditional probability densities together to form a combined conditional probability density; (e) determining checkout frequencies for the produce types; (f) determining probabilities for the types of produce items from the combined conditional probability density and the checkout frequencies; (f) determining a number of candidate identifications from the probabilities; and (g) identifying the produce item from the number candidate identifications.
Claim 2
Independent Claim
118 words
A method of identifying a produce item comprising the steps of: (a) collecting produce data from the produce item; (b) determining DML values between the produce data and reference produce data for a plurality of types of produce items; (c) determining conditional probability densities for all of the types of produce items using the DML values; (d) combining the conditional probability densities together to form a combined conditional probability density; (e) determining checkout frequencies for the produce types; (f) determining probabilities for the types of produce items from the combined conditional probability density and the checkout frequencies; (f) determining a number of candidate identifications from the probabilities; and (g) identifying the produce item from the number candidate identifications.
Claim 3
Dependent Claim
32 words
The method as recited in claim 1 , wherein step (g) comprises the substeps of: (g-1) displaying the candidate identifications; and (g-2) recording an operator selection of one of the candidate identifications.
Claim 4
Dependent Claim
18 words
The method as recited in claim 1 , wherein step (a) comprises the substep of: collecting spectral data.
Claim 5
Independent Claim
124 words
A method of identifying a produce item comprising the steps of: (a) collecting produce data from the produce item; (b) determining DML values between the produce data and reference produce data for a plurality of types of produce items; (c) determining conditional probability densities for all of the types of produce items using the DML values; (d) combining the conditional probability densities together to form a combined conditional probability density; (e) determining checkout frequencies for the produce types; (f) determining probabilities for the types of produce items from the combined conditional probability density and the checkout frequencies; (g) determining a number of candidate identifications from the probabilities; (h) displaying the candidate identifications; and (i) recording an operator selection of one of the candidate identifications.
Claim 6
Independent Claim
124 words
A method of identifying a produce item comprising the steps of: (a) collecting produce data from the produce item; (b) determining DML values between the produce data and reference produce data for a plurality of types of produce items; (c) determining conditional probability densities for all of the types of produce items using the DML values; (d) combining the conditional probability densities together to form a combined conditional probability density; (e) determining checkout frequencies for the produce types; (f) determining probabilities for the types of produce items from the combined conditional probability density and the checkout frequencies; (g) determining a number of candidate identifications from the probabilities; (h) displaying the candidate identifications; and (i) recording an operator selection of one of the candidate identifications.
Claim 7
Dependent Claim
113 words
A produce recognition system comprising: a number of sources of produce data for a produce item; and a computer system which determines DML values between the produce data and reference produce data for a plurality of types of produce items, determines conditional probability densities for all of the types of produce items using the DML values, combines the conditional probability densities together to form a combined conditional probability density, determines checkout frequencies for the produce types, determines probabilities for the types of produce items from the combined conditional probability density and the checkout frequencies, determines a number of candidate identifications from the probabilities, and identifies the produce item from the number candidate identifications.
Claim 8
Dependent Claim
113 words
A produce recognition system comprising: a number of sources of produce data for a produce item; and a computer system which determines DML values between the produce data and reference produce data for a plurality of types of produce items, determines conditional probability densities for all of the types of produce items using the DML values, combines the conditional probability densities together to form a combined conditional probability density, determines checkout frequencies for the produce types, determines probabilities for the types of produce items from the combined conditional probability density and the checkout frequencies, determines a number of candidate identifications from the probabilities, and identifies the produce item from the number candidate identifications.
Claim 9
Dependent Claim
27 words
The system as recited in claim 5 , wherein the computer system displays the candidate identifications and records an operator selection of one of the candidate identifications.
Claim 10
Dependent Claim
16 words
The system as recited in claim 6 , wherein one of the sources comprises a spectrometer.
References Cited (Backward Citations)
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2005-06-24 | 2005-12-24 | 2006-06-25 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2009-06-24 | 2009-12-24 | 2010-06-25 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2013-06-24 | 2013-12-24 | 2014-06-25 | $7700.00 | Window Closed / Lapsed |