A method and apparatus for correcting auto-exposure settings of a barcode reader based on modifying an auto-exposure region at a barcode reader for decoding a barcode in response to identifying a barcode and failing to decode the barcode due to incorrect initial exposure parameters, wherein the modified auto-exposure region is based at least in part on the barcode location.

There is provided an information processing apparatus. A first acquisition unit acquires first information concerning a size of a print region where a barcode is printed. A generation unit generates, based on the first information acquired by the first acquisition unit, image data of the barcode to be printed in the print region. The first information includes width information concerning a width of the print region and height information concerning a height of the print region. The generation unit generates the image data including, as a bar forming the barcode, a bar having a width based on the width information and a height based on the height information.

A system, method, and computer-readable medium for performing an encoded geometry fabrication operation. In various embodiments, the encoded geometry fabrication operation comprises: identifying data to be encoded within the encoded geometry, the data to be encoded within the encoded geometry comprising a unique code to be associated with the encoded geometry; converting the data to be encoded to the encoded geometry; fabricating a part with the encoded geometry, the encoded geometry passively representing the unique code with a physical code; and, performing a computer vision operation to read the physical code of the encoded geometry, the computer vision operation confirming the unique code of the encoded geometry corresponds to the physical code of the encoded geometry.

Methods for optimizing improper product barcode detection are disclosed herein. An example method, includes analyzing an object-based identification data against an indicia-based identification data to determine if there is a match. Responsive to there not being a match, entering a release condition state, where, instead of automatically sending a failed match signal to a symbology reader, a remote server awaits satisfaction of the release condition, before sending to the symbology reader. In some examples, a release condition is automatically satisfied by identifying a match in a subsequent comparison. In some examples, a user of the remote server is to satisfy the release condition.

Technology for generating, reading, and using machine-readable codes is disclosed. There is a method, performed by an image capture device, for reading and using the codes. The method includes obtaining an image, identifying an area in the image having a machine-readable code. The method also includes, within the image area, finding a predefined start marker defining a start point and a predefined stop marker defining a stop point, an axis being defined there between. A plurality of axis points can be defined along the axis. For each axis point, a first distance within the image area to a mark is determined. The distance can be measured from the axis point in a first direction which is orthogonal to the axis. The first distances can be converted to a binary code using Gray code such that each first distance encodes at least one bit of data in the code.

In one implementation, a processor: (1) receives an image of a candidate mark from an image acquisition device, (2) uses the image to measure one or more characteristics at a plurality of locations on the candidate mark, resulting in a first set of metrics, (3) removes, from the first set of metrics, a metric having a dominant amplitude, resulting in a trimmed first set of metrics, (4) retrieves, from a computer-readable memory, a second set of metrics that represents one or more characteristics measured at a plurality of locations on an original mark, (5) removes, from the second set of metrics, a metric corresponding to the metric removed from the first set of metrics, resulting in a trimmed second set of metrics, (6) compares the trimmed first set of metrics with the trimmed second set of metrics, and (7) determines whether the candidate mark is genuine based on the comparison.

A method and apparatus for correcting auto-exposure settings of a barcode reader based on modifying an auto-exposure region at a barcode reader for decoding a barcode in response to identifying a barcode and failing to decode the barcode due to incorrect initial exposure parameters, wherein the modified auto-exposure region is based at least in part on the barcode location.

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.

A system, method, and computer-readable medium for performing an encoded geometry fabrication operation. In various embodiments, the encoded geometry fabrication operation comprises: identifying data to be encoded within the encoded geometry, the data to be encoded within the encoded geometry comprising a unique code to be associated with the encoded geometry; converting the data to be encoded to the encoded geometry; fabricating a part with the encoded geometry, the encoded geometry passively representing the unique code with a physical code; and, performing a computer vision operation to read the physical code of the encoded geometry, the computer vision operation confirming the unique code of the encoded geometry corresponds to the physical code of the encoded geometry.

A tag comprises cells represented by marks, such as white and black, arranged in a predetermined pattern. Reference cells are used to determine the edges of the tag and orientation, while others are used to encode data and error correction data. During processing, a tag is detected based on a variability metric within a given region of an image exceeding a threshold value. Once detected, the orientation of the tag is determined using the reference cells. Confidence values, indicative of a likelihood that the cell is a particular cell value, such as white or black, are determined for each cell in a first set of cell values. If the first set is invalid, the cell values for a set of lowest confidence cell values are inverted to produce a second set of cell values. The second set is tested, and if valid, is used to produce output data.