A method is proposed of reading an optical code that encodes a message that has a character chain having a plurality of characters, said method comprising the steps: recording image data having the optical code; evaluating the image data with a reading of the optical code; comparing the read characters of the message with a scheme that contains a fixed character for at least one position of the message that is expected at this position in codes to be read; and recognizing an incorrectly read message and/or correcting the read message with reference to the comparison with the scheme. The scheme contains a variable character that is expected at this position in codes to be read for at least one position of the message, with a variable character being set to a partial range of the possible characters, but not to a fixed character.

In evaluation of the print quality of a symbol, the evaluation processing takes time. A symbol evaluation device (5) includes: a decoding unit (52) that decodes a symbol included in an image and thereby identifies reference position information of the symbol; a module position identification unit (53) that identifies a plurality of module positions included in the symbol on the basis of the reference position information of the symbol identified by the decoding unit; and a quality evaluation unit (54) that evaluates the quality of the symbol on the basis of the plurality of module positions identified by the module position identification unit.

Methods, apparatus, software and systems are disclosed for improved processing and especially sorting of mailpieces in order to reduce expensive manual steps. Mailpieces rejected during a first pass DPS sort, in one embodiment, are transferred to a special Reject Encoding Machine (REM) instead of a manual sort process. The REM preferably includes a labeling machine and on-board OCR engine, in order to read and barcode the reject mailpiece in a single processing step. This technique provides very fast turnaround so as to enable returning the mail to the DBCS in time to be included in the first pass run. In this way, the once rejected mailpieces are returned to resume automated processing.

A system and method for error correction for machine-readable symbols having data codewords, and having error correction (EC) codewords derived from the data codewords and redundantly indicating the location and data contents of the data codewords. The symbols use Reed-Solomon (RS) error correction to retrieve damaged codewords. RS error correction normally requires two EC codewords to identify both the location and data contents of a data codeword. The present system and method perform optical contrast analysis on the codewords, identifying those codewords with the lowest contrast levels. Codewords with the lowest contrast levels are flagged as optically ambiguous, thereby marking, in the EC equations, the locations of the codewords most like to be in error. As a result, only a single EC codeword is required to retrieve the data for a flagged data codeword.

An exemplary method of decoding a barcode uses a barcode template of known fixed fields in the barcode to enhance error correction in decoding of the barcode. A barcode having encoded data is scanned with an exemplary electronic device including a barcode scanner, a memory, and a barcode template stored in the memory. The barcode template includes fixed data fields and variable data fields. The barcode's encoded data are sampled into a codeword array, and a barcode template that matches the format of the scanned barcode is selected. Typically, error correction is then performed on the codeword array, and the error-corrected codeword array is then outputted.

Various embodiments illustrated herein disclose a method comprising receiving, by a processor, one or more patient characteristics associated with a first patient. The one or more patient characteristics comprises at least a type of sanitization, and/or a frequency of sanitization usage. Further, the method includes receiving one or more image characteristics associated with an image of a patient bracelet worn by the first patient. The method further includes training a machine learning (ML) model defining a relation between the one or more patient characteristics and the one or more image characteristics. The ML model is utilized to predict a count of days until the patient bracelet, associated with a second patient, deems unusable. Additionally, the method includes generating an instruction to a printing apparatus to print a new patient bracelet for the second patient based on the count of days being less than a predetermined number of days threshold.

To suppress an increase in processing time due to a load of inference processing while improving reading accuracy by the inference processing of machine learning. An optical information reading device includes a processor including: an inference processing part that inputs a code image to a neural network and executes inference processing of generating an ideal image corresponding to the code image; and a decoding processing part that executes first decoding processing of decoding the code image and second decoding processing of decoding the ideal image generated by the inference processing part. The processor executes the inference processing and the first decoding processing in parallel, and executes the second decoding processing after completion of the inference processing.

The optical information reader includes an imaging part configured to capture a plurality of images at predetermined timing until code reading results in success or a reading process times out, and an output part configured to output information on timing at which the optical information reader receives the trigger signal, success or failure information on code reading, and the plurality of images captured by the imaging part, and success or failure information representing whether the reading process performed by a decoder results in success or failure and the plurality of images captured in response to the trigger signal are associated with the trigger signal, and, with a list of reading results corresponding to a plurality of the trigger signals displayed on a display part.

Various embodiments illustrated herein disclose a method comprising receiving, by a processor, one or more patient characteristics associated with a first patient. The one or more patient characteristics comprises at least a type of sanitization, and/or a frequency of sanitization usage. Further, the method includes receiving one or more image characteristics associated with an image of a patient bracelet worn by the first patient. The method further includes training a machine learning (ML) model defining a relation between the one or more patient characteristics and the one or more image characteristics. The ML model is utilized to predict a count of days until the patient bracelet, associated with a second patient, deems unusable. Additionally, the method includes generating an instruction to a printing apparatus to print a new patient bracelet for the second patient based on the count of days being less than a predetermined number of days threshold.

A reading device, a reading method and a reading program that can easily and quickly read a composite symbol, and a settlement processing method are provided. A moving image of a composite symbol which includes a plurality of symbols emerging in the same location and whose appearance changes depending on a viewing angle, is captured. The symbols included in the composite symbol are detected from the moving image obtained by image-capturing. Authenticity of the composite symbol is determined based on the obtained moving image.