A method for extracting signatures and assigning signatory name attributions to the extracted signature images from unstructured digital documents is provided. The method includes: receiving a document that includes a signature; detecting a first region within the document in which the signature is present; applying a region-based convolutional neural network to the detected first region in order to demarcate a boundary that surrounds the detected first region; detecting a second region within the document in which a name that relates to the signature is present, by scanning the document to obtain a set of text words and then applying a named entity recognition (NER) machine learning algorithm to determine which text words are names; and assigning a signatory name attribution to the name that is present in the second region, based on a calculated distance between the name and the demarcated boundary.

A geographic object recognition unit (120) recognizes, using image data (192) obtained by photographing in a measurement region where a geographic object exists, a type of the geographic object from an image that the image data (192) represents. A position specification unit (130) specifies, using three-dimensional point cloud data (191) indicating a three-dimensional coordinate value of each of a plurality of points in the measurement region, a position of the geographic object.

A system and method are disclosed for using a local neighborhood for determining similar targets in different documents or using implicit coordinates for obtaining a coordinate location of a target. The local neighborhood method may include identifying a first target in a first document; identifying one or more first elements within a first distance range from the first target; creating a first local neighborhood based on the identifying; determining that that first local neighborhood is similar to a third local neighborhood in a second document; and determining a second target in the second document that corresponds to the first target in the first document, based on the determining the similarity. The implicit coordinates method may include performing OCR on the first document to find the first target; and obtaining a first location of the first target by using at least one of OCR or element recognition.

Disclosed herein are devices and methods for determining the identity of markings on tires. A portable tire scanner can comprise one or more light sources and detector that reflect light off tire markings and capture imagery of them. The scanner is operable to process the imagery to determine the identity of the markings. The marking can be the same color as the area of the tire around the marking (e.g., black-on-black) and the scanner can identify the marking by determining angular edges of the markings. Plural light sources and/or detectors can be used to provide plural perspectives to better determine the edges of the markings. The housing can have a form factor that allows the scanner to be hand-held, such that a user can aim the scanner at tires even while on a vehicle or in hard to reach positions. The scanner can be used to scan and identify several tire marking in succession.

According to an exemplary embodiment, a method for pre-cropping digital image data includes: dividing the digital image into segments; computing a color value distance between corresponding pixels of neighboring segments of the digital image; comparing the color value distance(s) against a minimum color distance threshold; clustering neighboring segments having a color value distance less than or equal to the minimum color distance threshold; computing a connected structure based on the clustered segments; computing a polygon bounding the connected structure; comparing a fraction of segments included in the connected structure and the polygon, relative to a total number of segments in the digital image, to a minimum included segment threshold; and in response to determining the fraction of segments in the connected structure and the polygon, relative to the total number of segments meets or exceeds a minimum included segment threshold, cropping the digital image based on edges of the polygon.

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; 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.

Systems, methods, and non-transitory computer-readable media can acquire an image that depicts at least one character. A set of pixels, within the image, through which the at least one character is depicted can be identified. At least one linear portion, within the image, can be identified based on the set of pixels. For each sub-portion within the at least one linear portion, a respective first confidence score representing a respective first likelihood that a respective sub-portion depicts the at least one character can be determined.

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.

Methods, apparatus, systems and articles of manufacture are disclosed for text extraction from a receipt image. An example non-transitory computer readable medium comprises instructions that, when executed, cause a machine to at least improve region of interest detection efficiency by converting pixels of an input receipt image from a first format to a second format, generate a binary representation of the input receipt image based on the converted pixels, the binary representation of the input receipt image corresponding to saturation values for respective ones of the converted pixels, calculate mirror data from the binary representation of the input receipt image, and cluster the binary representation of the input receipt image to identify a first set of candidate regions of interest, the candidate regions of interest characterized by portions of the binary representation of the input receipt image having saturation values that satisfy a threshold value.

A data generation apparatus includes: a separation unit that separates a serial number region and a background region from an original image of a paper currency that includes a serial number; a character image acquisition unit that identifies each of characters included in the separated serial number region, and acquires a character image of each of the identified characters; a background image acquisition unit that acquires a background image by complementing the serial number region in the separated background region; a pre-processing unit that generates a serial number image by combining the character images; an incorporation unit that incorporates the serial number image at a position corresponding to the serial number image in the background image; and an output unit that outputs image data in which the serial number that is combined by the pre-processing unit is associated with an incorporated image generated by the incorporation unit.