A method for correcting focus drift of an imaging system. The method includes an imaging system obtaining a plurality of images of an object of interest with each image obtained at a different focus of the imaging system. A processor then determines image property values of each image of the plurality of images and determines an image quality metric from each image of the plurality of images. The processor then compares the image quality metric to a reference metric and determines, based on the comparison, if a focus drift has occurred, and further adjusts a focus of the imaging system if a focus drift has occurred.

A payment processing system includes an imaging apparatus, a display apparatus, and a cash register. The imaging apparatus captures a first image in which an imaging target is captured. The display apparatus acquires the first image and displays a second image including identification information of the imaging target to an input unit of the cash register. The cash register specifies a type of the imaging target, based on the identification information. The second image is generated by object recognition processing or correction processing performed on the first image.

There is provided a barcode detection device including an image sensor and a processor. The image sensor captures an image frame of a barcode. The processor calculates a gradient vector of bars of the barcode in the image frame for determining a rotation angle of the image sensor. The rotation angle is used to calibrate a detected bar width.

An optical pattern is decoded in a scene. An automatic exposure feature of a camera is disabled. A first image is acquired and the optical pattern is detected in the first image. An exposure of the optical pattern in the first image is ascertained. At least one parameter of the camera is modified based on the exposure of the optical pattern. A second image is acquired using the modified parameter. The optical pattern in decoded in the second image.

Provided is a symbol reading device and a method capable of efficiently reading a symbol displayed on a paper medium and a display screen. The symbol reading device according to an embodiment includes: an image capturing unit; an illuminating unit configured to illuminate an image capturing region of the image capturing unit; a detecting unit configured to detect whether an object as an image capturing target is a non-light emitting medium or a light emitting medium based on an image captured by the image capturing unit; an illumination control unit configured to control an operation of the illuminating unit according to a detection result of the detecting unit; and a reading unit configured to read a symbol from the image captured by the image capturing unit.

The present disclosure relates to a system and method for improving scan rates of an item in a distribution network. The system may include an item scan database storing item scan datasets containing barcodes, item datasets and optical character recognition (OCR) labels datasets and a processor in data communication with the item scan database. The processor may detect an item barcode with an item orientation so as to output correct orientation information of the item. The processor may also extract available barcode information from the detected item barcode based on the correct orientation information of the item. The processor may further reconstruct a correct barcode from the extracted available barcode information and one or more of the item scan datasets.

A sufficient decoding processing time for each image acquired by performing high-speed imaging is secured to obtain a stable reading result, thereby enabling immediate output of the obtained reading result. A processing unit has a first core and a plurality of second cores. The first core instructs the second cores, presumed to be capable of immediately executing the decoding process or executing the decoding process next to a decoding process being currently executed, to execute the decoding process. The second cores are configured to be capable of simultaneously executing the decoding process on read images instructed by the first core at different timings.

A system performs a method for processing an image of a machine-readable code. The method includes receiving an image of a machine-readable code comprising coded information, where the machine-readable code is at least partially obscured. An adjusted image is generated by adjusting a color space of the image. At least a machine-readable code region of the image is binarized, wherein the machine-readable code region of the image depicts the machine-readable code. The binarized machine-readable code region is decoded to determine the coded information. Other apparatus and methods are also described.

The invention aims at reading, by a reading device, a 2D graphic code comprising zones including data zones encoding information based on real colours in a colour base and calibration zones presenting a predefined reference colour, the method comprising: optical acquisition of the 2D graphic code in current acquisition conditions to obtain image data, measuring of the observable colour in the calibration zones, spatial interpolation based on the observable colours in the calibration zones to estimate the theoretically observable colour for each base colour in the 2D graphic code, and classification based on the spatial interpolation for determining the real colour of analyzed data zones.

Embodiments related to local tone mapping for symbol reading. A local pixel neighborhood metric is determined for at least one raw pixel in a region-of-interest, which identifies on one or more raw pixels near the at least one raw pixel. A local mapping function is determined for the at least one raw pixel that maps the value of the raw pixel to a mapped pixel value with a mapped bit depth that is smaller than the bit depth associated with the raw image. The local mapping function is based on a value of at least one other raw pixel near the at least one raw pixel within the local pixel neighborhood metric, and at least one parameter determined based on the raw image. A mapped image is computed for the region-of-interest by applying the local mapping function to the raw image.