Abstract: A self-service terminal has a bin for storing media items. A mechanism is coupled to the bin that has a pathway for selectively conveying a media item from the bin to a dispenser. A heater device is mounted in the pathway for sanitizing the media item as it is conveyed to the dispenser. The heater device has a heating element set to a predetermined temperature and a roller driven by a motor set to move the media item past the heating element at a predetermined rate of speed. By selecting the predetermined temperature to 116° C. and the predetermined rate of speed to 181 mm/sec, 99.9999% of the viral load of a known type pathogen, i.e., SARS-CoV-2, is eliminated from the media item by the sanitization process.

Abstract: A self-service terminal has a bin for storing media items. A mechanism is coupled to the bin that has a pathway for selectively conveying a media item from the bin to a dispenser. A heater device is mounted in the pathway for sanitizing the media item as it is conveyed to the dispenser. The heater device has a heating element set to a predetermined temperature and a roller driven by a motor set to move the media item past the heating element at a predetermined rate of speed. By selecting the predetermined temperature to 116° C. and the predetermined rate of speed to 181 mm/sec, 99.9999% of the viral load of a known type pathogen, i.e., SARS-CoV-2, is eliminated from the media item by the sanitization process.

Abstract: Decentralized cameras perform video tracking on captured video. The cameras produce metadata representing tracking of objects from the captured video. The metadata is passed between the cameras as the object moves within the captured video. Final metadata from at least one of the cameras is sent to a server, the server processes the final metadata to produce a summary of the object tracking and process one or more automated actions based on the summary.

Abstract: A method of optimizing a pick list using image data from a barcode scanner. An example method includes comparing a reference background image captured by a scanner to an image of a produce item to be purchased, calculating attributes from the image, comparing the calculated attributes to reference produce attributes in a produce database, selecting reference produce attributes associated with reference produce items that are closest to the calculated attributes as the top candidates in the pick list.

Abstract: An image is compared to a validation image to obtain a signal-to-noise ratio. The signal-to-noise ratio is used to determine validity of the image. According to an embodiment, the image includes a barcode. According to another embodiment, a minimum threshold value for the signal-to-noise ratio is set and the validity of the image is determined based on the minimum threshold value and the signal-to-noise ratio. The minimum threshold value can be determined by using respective signal-to-noise ratios resulting from comparing a valid image to a validation image and an invalid image to a validation image.

Abstract: Decentralized cameras perform video tracking on captured video. The cameras produce metadata representing tracking of objects from the captured video. The metadata is passed between the cameras as the object moves within the captured video. Final metadata from at least one of the cameras is sent to a server, the server processes the final metadata to produce a summary of the object tracking and process one or more automated actions based on the summary.

Abstract: Various embodiments herein each include at least one of systems, methods, software, and devices, such as product scanners e.g., barcode scanners) enabled to detect item substitution fraud during a checkout process at facilities, such as retail outlets. One method embodiment that may be performed in part on a product scanner, includes detecting, on a point-of-sale (POS) terminal, an event occurrence associated with at least one validation process. The method may then receive an image from each of at least one camera of a plurality of cameras of the product scanner. The method further includes processing at least one of the received images according to the at least one validation process to obtain a result and providing the result to the POS terminal.

Abstract: An image is compared to a validation image to obtain a signal-to-noise ratio. The signal-to-noise ratio is used to determine validity of the image. According to an embodiment, the image includes a barcode. According to another embodiment, a minimum threshold value for the signal-to-noise ratio is set and the validity of the image is determined based on the minimum threshold value and the signal-to-noise ratio. The minimum threshold value can be determined by using respective signal-to-noise ratios resulting from comparing a valid image to a validation image and an invalid image to a validation image.

Abstract: An image is compared to a validation image to obtain a signal-to-noise ratio. The signal-to-noise ratio is used to determine validity of the image. According to an embodiment, the image includes a barcode. According to another embodiment, a minimum threshold value for the signal-to-noise ratio is set and the validity of the image is determined based on the minimum threshold value and the signal-to-noise ratio. The minimum threshold value can be determined by using respective signal-to-noise ratios resulting from comparing a valid image to a validation image and an invalid image to a validation image.

Abstract: A method of optimizing a pick list using image data from a barcode scanner. An example method includes comparing a reference background image captured by a scanner to an image of a produce item to be purchased, calculating attributes from the image, comparing the calculated attributes to reference produce attributes in a produce database, selecting reference produce attributes associated with reference produce items that are closest to the calculated attributes as the top candidates in the pick list.

Abstract: Various embodiments herein each include at least one of systems, methods, software, and devices, such as product scanners e.g., barcode scanners) enabled to detect item substitution fraud during a checkout process at facilities, such as retail outlets. One method embodiment that may be performed in part on a product scanner, includes detecting, on a point-of-sale (POS) terminal, an event occurrence associated with at least one validation process. The method may then receive an image from each of at least one camera of a plurality of cameras of the product scanner. The method further includes processing at least one of the received images according to the at least one validation process to obtain a result and providing the result to the POS terminal.

Abstract: Methods and apparatus are provided for fast item identification. A plurality of sensors capture data for an unknown item that is moved past the sensors. The data is processed to produce a plurality of physical attributes related to the unknown item. The physical attributes are used to search a database of physical attributes for a large number of known items where the unknown item is one of the known items. A small set of known items are selected where the physical attributes of the known items match the physical attributes of the unknown item. Further processing of the selected set of known items identifies the unknown item as one of the set of known items.

Abstract: An image is compared to a validation image to obtain a signal-to-noise ratio. The signal-to-noise ratio is used to determine validity of the image. According to an embodiment, the image includes a barcode. According to another embodiment, a minimum threshold value for the signal-to-noise ratio is set and the validity of the image is determined based on the minimum threshold value and the signal-to-noise ratio. The minimum threshold value can be determined by using respective signal-to-noise ratios resulting from comparing a valid image to a validation image and an invalid image to a validation image.

Abstract: An optical code scanner is presented that includes image capture technology to read optical codes. The optical code scanner captures an image of an optical code and then generates multiple reduced resolution versions of the image. Multiple techniques are applied to the different images to identify a region of interest, enhance the contrast of the image, perform a non-linear local geometrical distortion correction and minimize the spatial resolution required to read the optical code. The techniques reduce the raw processing power and time required to identify and read an optical code.

Abstract: A apparatus, method, and system for reading an optical code using a multiple path image scanner. The image scanner captures a plurality of images using multiple optical image paths and a path directing device that directs the images to an image capture device. One or more of the captured images is then used to decode the optical code.

Abstract: An optical code scanner is presented that includes image capture technology to read optical codes. The optical code scanner captures an image of an optical code and then generates multiple reduced resolution versions of the image. Multiple techniques are applied to the different images to identify a region of interest, enhance the contrast of the image, perform a non-linear local geometrical distortion correction and minimize the spatial resolution required to read the optical code. The techniques reduce the raw processing power and time required to identify and read an optical code.

Abstract: Methods and apparatus are provided for low resolution item identification. An image of an unknown item is captured and quantized to greatly lower the resolution of the image. The quantized image data of the unknown item is compared to a plurality of the quantized image data for known items. The comparison includes using a signal-to-noise ratio calculated using the quantized image data for both the unknown and known items. A match is found when the calculated signal-to-noise ratio is above a predetermined threshold value.

Abstract: Systems and techniques for automated checkout verification. Product identification information is received and used as an index to retrieve a set of images associated with the identified product. The images may provide multiple views of the product. As the product is presented for purchase, an image of the product is captured and compared with the set of retrieved images. If it is determined that the captured image does not match the set of retrieved images, a security alert is issued.

Abstract: Methods and apparatus are provided for low resolution item identification. An image of an unknown item is captured and quantized to greatly lower the resolution of the image. The quantized image data of the unknown item is compared to a plurality of the quantized image data for known items. The comparison includes using a signal-to-noise ratio calculated using the quantized image data for both the unknown and known items. A match is found when the calculated signal-to-noise ratio is above a predetermined threshold value.

Abstract: Methods and apparatus are provided for fast item identification. A plurality of sensors capture data for an unknown item that is moved past the sensors. The data is processed to produce a plurality of physical attributes related to the unknown item. The physical attributes are used to search a database of physical attributes for a large number of known items where the unknown item is one of the known items. A small set of known items are selected where the physical attributes of the known items match the physical attributes of the unknown item. Further processing of the selected set of known items identifies the unknown item as one of the set of known items.