A system comprising one or more processors, and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations comprising: displaying, one or more instructions on a user interface of a mobile device to instruct a user to capture each respective image of a prescription label; determining, using contrast, a location of each respective image in the set of images that is associated with the respective different portions of the prescription label on the medication package; reconstructing each of the respective different portions of the prescription label on the medication package as a flattened reconstruction of the respective different portions of the prescription label; and providing for display on the user interface a reconstructed prescription label. Other embodiments are disclosed herein.

An image processing apparatus that generates an image for character recognition from a read image includes at least one memory that stores instructions, and at least one processor that executes the instructions to perform extracting of an area of handwritten character information and an area of printed character information from the read image, clipping of a partial image of the area of handwritten character information and a partial image of the area of printed character information out of the read image, and generating of the image for character recognition by combining the partial image of the area of handwritten character information and the partial image of the area of printed character information being associated with each other.

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.

Aspects of the present disclosure provide methods and apparatuses for processing a digital image of a document, for example, to determine whether the document is a long document. An exemplary method generally includes obtaining a plurality of digital images of the document, determining a type of the document, loading one or more pre-defined metrics associated with the document based on the determined type of the document, determining one or more characteristics of the document based on one or more analyses performed on the plurality of digital images of the document, comparing the one or more characteristics of the document with the one or more pre-defined metrics, and determining the document to be a long document based, at least in part, on the comparison.

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 computer-implemented method including detecting respective one or more text boxes in each of multiple partial images of a text-bearing area. The method also can include determining respective one or more edge text boxes of the respective one or more text boxes in each of overlapping partial images of the multiple partial images, wherein each of the respective one or more edge text boxes comprise a respective incomplete text. The method additionally can include matching one or more pairs of corresponding edge text boxes from the respective one or more edge text boxes of two adjacent images of the overlapping partial images of the multiple partial images. The method also can include determining cross-image texts in the one or more pairs of the corresponding edge text boxes. The method further can include determining one or more entities in the text-bearing area based on entity texts of the cross-image texts and non-edge texts in respective one or more non-edge text boxes of the respective one or more text boxes in the multiple partial images. Other embodiments are described.

Systems and methods for reconstructing a document from a series of document images. An example method comprises: receiving a plurality of image frames, wherein each image frame of the plurality of image frames contains at least a part of an image of an original document; identifying a plurality of visual features in the plurality of image frames; performing spatial alignment of the plurality of image frames based on matching the identified visual features; splitting each of the plurality of image frames into a plurality of image fragments; identifying one or more text-depicting image fragments among the plurality of image fragments; associating each identified text-depicting image fragment with an image frame in which that image fragment has an optimal value of a pre-defined quality metric among values of the quality metric for that image fragment in the plurality of image frames; and producing a reconstructed image frame by blending image fragments from the associated image frames.

Aspects of the present disclosure provide methods and apparatuses for processing a digital image of a document, for example, to determine whether the document is a long document. An exemplary method generally includes obtaining a plurality of digital images of the document, determining a type of the document, loading one or more pre-defined metrics associated with the document based on the determined type of the document, determining one or more characteristics of the document based on one or more analyses performed on the plurality of digital images of the document, comparing the one or more characteristics of the document with the one or more pre-defined metrics, and determining the document to be a long document based, at least in part, on the comparison.

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 method for optical character recognition (OCR) on a surface, comprising: activating an image capture device; scanning the surface to obtain 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 these layers into single layers; and combining the single layers into a unified image.