System and method for estimation and classification of barcodes using heuristic and statistical measures
In a system and method of estimating and classifying a barcode using heuristic and statistical measures, a classification determination is generated for each of a plurality of estimated barcode digits that correspond to a decoded barcode estimation. The classification determination is selected from one of a first classification determination and a second classification determination. The first classification determinations among a plurality of estimation determinations are aggregated. The aggregated first classification determinations are compared to a first predetermined threshold to determine a validity of the decoded barcode estimation.
1. A system, comprising:
a processor-implemented barcode classifier module configured to:
generate a classification determination for each of a plurality of estimated barcode digits corresponding to an estimated decoded barcode, the classification determination being one of a first classification determination and a second classification determination, and the classification determination being generated by calculating a noise-to-signal ratio of a best barcode digit estimate to a second-best barcode digit estimate and comparing the noise-to-signal ratio to a first predetermined threshold value; and
aggregate first classification determinations among a plurality of classification determinations for the plurality of estimated barcode digits; and
a processor-implemented barcode comparator module configured to compare the aggregated first classification determinations with a second predetermined threshold to determine a validity of the decoded barcode estimation.
2. The system of claim 1 , wherein the classification determination is the first classification determination based on the noise-to-signal ratio being lower than the first predetermined threshold value, and wherein the classification determination is the second classification determination based on the noise-to-signal ratio being not lower than the first predetermined threshold value.
3. The system of claim 1 , wherein the first classification determination indicates that the estimated barcode digit is likely accurate, and wherein the second classification determination indicates that the estimated barcode digit is likely inaccurate.
4. The system of claim 1 , wherein the decoded barcode estimation is determined to be likely correct based on the aggregated first classification determinations being greater than the second predetermined threshold, and wherein the decoded barcode estimation is determined to be likely incorrect based on the aggregated first classification determinations being not greater than the second predetermined threshold.
5. The system of claim 1 , further comprising a processor-implemented communication module configured to transmit a portion of the decoded barcode estimation to a server via a network and receive confirmation of an existence of a barcode corresponding to the decoded barcode estimation.
6. The system of claim 1 , wherein the second predetermined threshold is generated from a set of decoded barcodes.
7. The system of claim 1 , further comprising a processor-implemented barcode decoder module configured to generate the decoded barcode estimation from a stream of video frames.
8. A computer-implemented method, comprising:
generating a classification determination for each of a plurality of estimated barcode digits corresponding to a decoded barcode estimation, the classification determination being one of a first classification determination and a second classification determination, and the classification determination being generated by calculating a noise-to-signal ratio of a best barcode digit estimate to a second-best barcode digit estimate and comparing the noise-to-signal ratio to a first predetermined threshold value;
aggregating first classification determinations among a plurality of classification determinations for the plurality of estimated barcode digits; and
comparing the aggregated first classification determinations with a second predetermined threshold to determine a validity of the decoded barcode estimation.
9. The computer-implemented method of claim 8 , wherein the classification determination is the first classification determination based on the noise-to-signal ratio being lower than the first predetermined threshold value, and wherein the classification determination is the second classification determination based on the noise-to-signal ratio being not lower than the first predetermined threshold value.
10. The computer-implemented method of claim 8 , wherein the first classification determination indicates that the estimated barcode digit is likely accurate, and wherein the second classification determination indicates that the estimated barcode digit is likely inaccurate.
11. The computer-implemented method of claim 8 , wherein the decoded barcode estimation is likely correct based on the aggregated first classification determinations being greater than the second predetermined threshold, and wherein the decoded barcode estimation is likely incorrect based on the aggregated first classification determinations being not greater than the second predetermined threshold.
12. The computer-implemented method of claim 8 , further comprising:
transmitting a portion of the decoded barcode estimation to a server via a network; and
receiving confirmation of an existence of a barcode corresponding to the decoded barcode estimation.
13. The computer-implemented method of claim 8 , wherein the second predetermined threshold is generated from a set of decoded barcodes.
14. A non-transitory machine-readable storage medium storing a set of instructions that, when executed by a machine, causes the machine to perform operations, comprising:
generating a classification determination for each of a plurality of estimated barcode digits corresponding to a decoded barcode estimation, the classification determination being one of a first classification determination and a second classification determination and the classification determination being generated by calculating a noise-to-signal ratio of a best barcode digit estimate to a second-best barcode digit estimate and comparing the noise-to-signal ratio to a first predetermined threshold value;
aggregating first classification determinations among a plurality of classification determinations for the plurality of estimated barcode digits; and
comparing the aggregated first classification determinations with a second predetermined threshold to determine a validity of the decoded barcode estimation.
15. The non-transitory machine-readable storage medium of claim 14 , wherein the classification determination is the first classification determination based on the noise-to-signal ratio being lower than the first predetermined threshold value, and wherein the classification determination is the second classification determination based on the noise-to-signal ratio being not lower than the first predetermined threshold value.
16. The non-transitory machine-readable storage medium of claim 14 , wherein the first classification determination indicates that the estimated barcode digit is likely accurate, and wherein the second classification determination indicates that the estimated barcode digit is likely inaccurate.
17. The non-transitory machine-readable storage medium of claim 14 , wherein the decoded barcode estimation is likely correct based on the aggregated first classification determinations being greater than the second predetermined threshold, and wherein the decoded barcode estimation is likely incorrect based on the aggregated first classification determinations being not greater than the second predetermined threshold.
18. The non-transitory machine-readable storage medium of claim 14 , further comprising:
transmitting a portion of the decoded barcode estimation to a server via a network; and
receiving confirmation of an existence of a barcode corresponding to the decoded barcode estimation.
19. The non-transitory machine-readable storage medium of claim 14 , wherein the second predetermined threshold is generated from a set of decoded barcodes.