Abstract: Systems and methods for detecting and decoding 4-state barcodes with extreme bar dilation are disclosed. The method is implemented in a computing device and includes: separating an extracted image of a barcode into a top half and a bottom half; estimating bar positions and then sampling heights of the top and bottom images at each position; using adjacent bar height differences to determine the top and bottom of the tracker portion for each bar position; removing the tracker contribution to the top and bottom heights at each bar position; sending the resulting sequence of bars with ascender and descender information to a decoder for decoding processes.

Abstract: A computer-implemented method includes: receiving, by a computing device, sensor data associated with a geographic location; processing, by the computing device, the sensor data to identify an infrastructure asset within the geographic location; determining, by the computing device, a condition of the infrastructure asset based on processing the sensor data; and storing or outputting, by the computing device, information regarding the condition of the infrastructure asset.

Abstract: A computer-implemented method includes: receiving, by a computing device, sensor data associated with a geographic location; processing, by the computing device, the sensor data to identify an infrastructure asset within the geographic location; determining, by the computing device, a condition of the infrastructure asset based on processing the sensor data; and storing or outputting, by the computing device, information regarding the condition of the infrastructure asset.

Abstract: Systems and methods for detecting and decoding 4-state barcodes with extreme bar dilation are disclosed. The method is implemented in a computing device and includes: separating an extracted image of a barcode into a top half and a bottom half; estimating bar positions and then sampling heights of the top and bottom images at each position; using adjacent bar height differences to determine the top and bottom of the tracker portion for each bar position; removing the tracker contribution to the top and bottom heights at each bar position; sending the resulting sequence of bars with ascender and descender information to a decoder for decoding processes.

Abstract: A method to reduce lost postal revenue by identifying and sorting a mail piece by determining whether algorithmically-resolved image data corresponding to the mail piece indicates that the mail piece is business reply mail. The method is facilitated in part by maintaining data related to each business reply customer account. The business reply customer data is consulted and compared to a predetermined set of criteria to ascertain if the possibly incomplete, incorrect, or ambiguous data discernable from the captured image of the mail piece is indicative of, at a minimum, that the mail piece is business reply for the purpose of sortation to an appropriate business reply collection point, and in addition, that a high-confidence match to a customer account can be obtained for the purpose of automated charge assessment. Machine-readable sortation signals are generated in accordance with the most refined level of sortation indicated by the consultation.

Abstract: A method to reduce lost postal revenue by identifying and sorting a mail piece by determining whether algorithmically-resolved image data corresponding to the mail piece indicates that the mail piece is business reply mail. The method is facilitated in part by maintaining data related to each business reply customer account. The business reply customer data is consulted and compared to a predetermined set of criteria to ascertain if the possibly incomplete, incorrect, or ambiguous data discernable from the captured image of the mail piece is indicative of, at a minimum, that the mail piece is business reply for the purpose of sortation to an appropriate business reply collection point, and in addition, that a high-confidence match to a customer account can be obtained for the purpose of automated charge assessment. Machine-readable sortation signals are generated in accordance with the most refined level of sortation indicated by the consultation.

Abstract: The processing of mail pieces relies in part on automated address interpretation of captured address field images to generate sortation signals that control automated mail sorting machinery at outgoing and incoming mail centers. In alternative implementations, a coding depth file (“CDF”) controls (i) the depth to which a captured address field image is resolved and (ii) a time delay in performing address interpretation. In one aspect, a CDF includes a first set of data associating a depth value with each of a selected plurality of incoming mail centers to which an outgoing mail center sends mail pieces. The depth value controls the depth to which a stored address field image is resolved and corresponds to a level of refinement to which automated sorting machinery at the associated incoming mail center sorts mail pieces.

Abstract: The processing of mail pieces relies in part on automated address interpretation of captured address field images to generate sortation signals that control automated mail sorting machinery at outgoing and incoming mail centers. In alternative implementations, a coding depth file (“CDF”) controls (i) the depth to which a captured address field image is resolved and (ii) a time delay in performing address interpretation. In one aspect, a CDF includes a first set of data associating a depth value with each of a selected plurality of incoming mail centers to which an outgoing mail center sends mail pieces. The depth value controls the depth to which a stored address field image is resolved and corresponds to a level of refinement to which automated sorting machinery at the associated incoming mail center sorts mail pieces.