Methods for managing notes, either digital notes or images of physical notes. The methods use optical character recognition to convert handwritten content into characters and icons. The methods also determine sizes of non-square physical notes when imaged by a camera from various angles. For curled notes or damaged notes such as a note missing a corner, the methods detect and process edges of a physical note in an image and, using the detected edges, convert the image of the physical note into a corresponding digital note without curl or damage.

Methods for managing notes, either digital notes or images of physical notes. The methods use optical character recognition to convert handwritten content into characters and icons. The methods also determine sizes of non-square physical notes when imaged by a camera from various angles. For curled notes or damaged notes such as a note missing a corner, the methods detect and process edges of a physical note in an image and, using the detected edges, convert the image of the physical note into a corresponding digital note without curl or damage.

An image processing apparatus counts at least one of the number of pixels having an identical color to a target pixel, the number of pixels having a similar color to the target pixel, and the number of pixels having a different color from the target pixel in a target window, and determines an attribute of the target pixel based on a result of the counting.

A method, system and device for inspection of a lottery ticket uses a device to scan lottery tickets to detect information concerning the amount of scratch-off material, such as a coating or a covering, that has been removed from a ticket, and/or the type, amount, or content of underlying indicia that have been revealed by the scratches. The system may use the information to calculate and set or determine a tolerance level for scratching below which a ticket will not be invalidated, based on parameters that may include the amount of surface area that has been scratched, and/or the type, amount, or content of underlying indicia that has been revealed. The system enables a user to input information to reset the threshold volume to a user-selected volume above which invalidation is triggered.

A method, system and device for inspection of a lottery ticket uses a device to scan lottery tickets to detect information concerning the amount of scratch-off material, such as a coating or a covering, that has been removed from a ticket, and/or the type, amount, or content of underlying indicia that have been revealed by the scratches. The system may use the information to calculate and set or determine a tolerance level for scratching below which a ticket will not be invalidated, based on parameters that may include the amount of surface area that has been scratched, and/or the type, amount, or content of underlying indicia that has been revealed. The system enables a user to input information to reset the threshold volume to a user-selected volume above which invalidation is triggered.

An imaging processing device includes a processor. The processor performs processing of acquiring a captured image which is captured in a state where a light source emits light, extracting an overexposed portion which occurs in the captured image due to the light emission of the light source and which has a predetermined pixel value or more, and setting a region located in an area, which does not overlap with the extracted overexposed portion in the captured image, as a region of a collation target to be collated with a predetermined reference image.

Some aspects of the disclosure provide a method for image processing. The method includes receiving one or more first images corresponding to first portions in a section of characters for recognition, splicing the one or more first images into a first intermediate spliced image and performing a first intermediate character recognition on the first intermediate spliced image based on a first optical character recognition model. The first intermediate character recognition generates a first intermediate recognition result for display. The method further includes performing a final character recognition on a final spliced image corresponding to the section of characters for recognition based on a second optical character recognition model that is different from the first optical character recognition model. The final character recognition generates a final recognition result of the section of characters. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.

Some aspects of the disclosure provide a method for image processing. The method includes receiving one or more first images corresponding to first portions in a section of characters for recognition, splicing the one or more first images into a first intermediate spliced image and performing a first intermediate character recognition on the first intermediate spliced image based on a first optical character recognition model. The first intermediate character recognition generates a first intermediate recognition result for display. The method further includes performing a final character recognition on a final spliced image corresponding to the section of characters for recognition based on a second optical character recognition model that is different from the first optical character recognition model. The final character recognition generates a final recognition result of the section of characters. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.

This application discloses a data processing method and apparatus, a computer device, and a non-transitory computer-readable storage medium in the technical field of computers. This application, for textual data and picture data of an article, extracts a textual feature and a picture feature, respectively, and predicts an article classification to which the article belongs using a cross-modal interaction feature between the textual feature and picture feature. At the same time, this application considers the contribution degree of each of a textual modality and a picture modality to the article classification, rather than determining from a textual perspective only. In addition, the extracted cross-modal interaction feature is not a simple concatenation of the textual feature and the picture feature, which can reflect richer and deeper inter-modal interaction information, and greatly improve the identification accuracy of the article classification. Furthermore, it can improve the discovering accuracy of high-quality articles in the scene of identifying high-quality articles.

This application discloses a data processing method and apparatus, a computer device, and a non-transitory computer-readable storage medium in the technical field of computers. This application, for textual data and picture data of an article, extracts a textual feature and a picture feature, respectively, and predicts an article classification to which the article belongs using a cross-modal interaction feature between the textual feature and picture feature. At the same time, this application considers the contribution degree of each of a textual modality and a picture modality to the article classification, rather than determining from a textual perspective only. In addition, the extracted cross-modal interaction feature is not a simple concatenation of the textual feature and the picture feature, which can reflect richer and deeper inter-modal interaction information, and greatly improve the identification accuracy of the article classification. Furthermore, it can improve the discovering accuracy of high-quality articles in the scene of identifying high-quality articles.