The system captures portions of a label on a package in a set of images, reconstructs the label based on the set of images, identifies text in the label, determines associations of identified text and types of information, and stores the set of images, the reconstructed label, the identified text in the label, and the determined associations as, for example, a batch in a review queue. During a review process, the batch is reviewed and a structured prescription record is determined for the batch which is further used by the system and user of the system associated with the batch to provide various features to the user.

A recognition method and apparatus, and an electronic device are provided. The recognition method includes: adjusting shooting parameters of a camera in a case that a collected first image includes a light reflecting region, where the shooting parameters include at least one of an aperture and a focus; collecting a second image according to adjusted shooting parameters; and recognizing the target image to obtain a corresponding recognition result, where the target image includes the second image, or the target image is obtained based on the first image and the second image.

A method of identifying and analyzing contiguities in images is disclosed. The contiguities are indicative features and various qualities of an image, which may be used for identifying objects and/or relationships in images. Alternatively, the contiguities may be helpful in ensuring that an image has a desired figure-ground ambiguous switch between percepts, so as to create a desired effect when combined with other images to generate a composite image set. The contiguity may be a group of picture elements that are adjacent to one another that form a continuous image element that extends generally horizontally (e.g., diagonally, horizontally and/or vertically) across the image.

A marking region image is obtained by cutting out the part corresponding to a marking region from an article image obtained by imaging an article to be inspected. Then, whether or not the marking is properly provided is determined by performing a character recognition of a marking part for a marking region image. Further, an image of an article having no marking and no defect is stored as a reference image, whereas a marking periphery image obtained by removing the image of the marking part from the marking region image is compared to the reference image. By that comparison, whether or not any defect is included in the marking peripheral part of the marking region except the marking part is determined.

A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

A delivery system may include a pallet wrapper system having a turntable, a camera directed toward an area above the turntable, and a stretch wrap dispenser adjacent the turntable. A computer receives images from the camera of multiple sides of a pallet loaded with packages on the turntable. The computer stitches images from different sides of the stack of packages that correspond to the same package. At least one machine learning model may be used to infer SKUs of each package. Optical character recognition may be performed in parallel on the images. The determination of the SKU of each package may be based upon the inferred SKUs and on the OCR.

Methods and apparatus for blending unknown pixels in overlapping images. In one embodiment, an action camera captures two hyper-hemispherical fisheye images that are stitched to a 360° panorama. In order to remove exposure differences between the two cameras, the images are pre-processed prior to multiband blending. The pre-processing leverages image information from pixels to make informed guesses about pixels that were not captured. In particular, various pixels with different knowability (e.g., known, unknown, consistent, and conflicting) may be handled differently so as to emphasize/de-emphasize their importance in pre-processing.

A method for optical character recognition of text and information on a curved surface, comprising: activating an image capture device; scanning of the surface using the image capture device in order to acquire a plurality of scans of sections of the surface; performing OCR on the plurality of scans; separating the OCRed content into layers for each of the plurality of scans; merging the separated layers into single layers; and merging the single layers into an image.

A glare reducing optical recognition system that recognizes alphanumeric text wherein the system includes a first light emitter that emits light in a first direction and a second light emitter that emits light in a second direction different from the first direction. The system includes an image capturing device that captures a first image of alphanumeric text illuminated by the first light emitter emitting light in the first direction, and a second image of the alphanumeric text illuminated by the second light emitter emitting light in the second direction. The system includes an image processor that constructs a glare reduced image by comparing sections of the first image with corresponding sections of the second image and selecting the section with the least luminosity to populate the corresponding section of the glare reduced image. The system may include a character recognition processor, a label producing apparatus, and/or a conveyance system.