Methods, apparatus, systems, and articles of manufacture are disclosed that decode purchase data using an image. An example apparatus includes a dictionary including associated product descriptions and barcodes, interface circuitry, and processing circuitry to execute machine readable instructions to obtain purchase details and barcodes corresponding to a receipt, the purchase details including receipt product descriptions, generate a search query that includes a first receipt product description of the receipt product descriptions, a list of barcodes corresponding to the barcodes, and a store identifier associated with the receipt, execute a search against the dictionary using the search query to identify a barcode from the list of barcodes that corresponds to the first receipt product description, and in response to identifying the barcode that corresponds to the first receipt product description, associating the barcode and the first receipt product description and adding the association to the dictionary.

Methods and apparatus to determine the dimensions of a region of interest of a target object and a class of the target object from an image using target object landmarks are disclosed herein. An example method includes identifying a landmark of a target object in an image based on a match between the landmark and a template landmark; classifying a target object based on the identified landmark; projecting dimensions of the template landmark based on a location of the landmark in the image; and determining a region of interest based on the projected dimensions, the region of interest corresponding to text printed on the target object.

A method and computing apparatus for verifying an operability of a target device are provided. The method includes sequentially obtaining first image information of the target device, initiating a communication with the target device, obtaining second image information of the target device, comparing the first image information with the second image information; and determining whether the target device is operational based on a result of the comparing wherein the target device is determined as being operational when the first image information is different from the second image information, and the target device is determined as at least one of not receiving communications and not operational when the first image information is identical to the second image information.

Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image, wherein each of the first plurality of pixels is located in a background region of the digital image; optionally sampling color information from a second plurality of pixels of the digital image, wherein each of the second plurality of pixels is located in a foreground region of the digital image; assigning each pixel a label of either foreground or background using an adaptive label learning process; binarizing the digital image based on the labels assigned to each pixel; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.

Embodiments facilitate selection and assignment of a known user model, based upon input comprising table images of original data. A table engine receives the image and performs pre-processing (e.g., rasterization, Optical Character Recognition, coordinate representation) thereupon to identify image entities. After filtering original numerical data, a similarity (e.g., a distance) is calculated between an image entity and a dimension member of the known user model. Based upon this similarity, the table engine selects and assigns the known user model to the incoming tables images, generating a file representing table columns and rows. This file is received at the UI of an analytics platform, which in turn populates the model with data of the user (rather than the original data) via an API. Embodiments may be particularly valuable in allowing a user to rapidly generate multi-dimensional tables comprising their own data, based upon raw table images received from an external party.

An apparatus, method, and computer readable medium for generating and displaying a dynamic language translation overlay that include accessing a frame buffer of the GPU, analyzing, in the frame buffer of the GPU, a frame representing a section of a stream of displayed data that is being displayed by a display device, based on the analyzed frame, identifying a reference patch that includes an instruction to identify an object comprising original text, based on the instruction included in the reference patch, recognizing the original text, generating translated text, generating an overlay comprising an augmentation layer, the augmentation layer including the translated text, and overlaying the overlay, onto the displayed data such that the translated text is viewable while the original text is obscured from view.

An image processing apparatus comprises an execution unit configured to selectively execute, for each pixel in each of a first region, a second region, and an intermediate region, one of a plurality of processes including first processing of generating an output value indicating that a first printing material is applied and a second printing material of a color different from a color of the first printing material is not applied, and second processing of generating an output value indicating that the second printing material is applied.

Systems as described herein may include predicting item level data based on merchant advertisement information. A transaction pattern may be detected. The merchant advertisement information may be retrieved and parsed to generate a price list. A number of transactions that each shares a common payment amount may be determined and the number may reach a threshold value. Items from the price list may be matched with the common payment amount. The transaction records may be updated to indicate likely item level transaction information. In a variety of embodiments, the likely transaction information may be presented to a user.

A focus detection method includes: acquiring an image of a test object through a to-be-tested image acquisition device, the test object including a character, and a clarity of the character corresponding to a minimum clarity with which a content of the character is still able to be recognized using a character recognition technology; performing character recognition on the image to obtain a recognition result; and determining a focus detection result for the to-be-tested image acquisition device based on the recognition result.

An image processing system according to the present embodiment acquires a processing target image read from an original that is handwritten and specifies one or more handwritten areas included in the acquired processing target image. In addition, for each specified handwritten area, the present image processing system extracts from the processing target image a handwritten character image and a handwritten area image indicating an approximate shape of a handwritten character. Furthermore, for a handwritten area including a plurality of lines of handwriting among the specified one or more handwritten areas, a line boundary of handwritten characters is determined from a frequency of pixels indicating a handwritten area in a line direction of the handwritten area image, and a corresponding handwritten area is separated into each line.