Abstract:
According to one embodiment, a computer-implemented method is configured for building a classification and/or data extraction knowledge base using an electronic form. The method includes: receiving an electronic form having associated therewith a plurality of metadata labels, each metadata label corresponding to at least one element of interest represented within the electronic form; parsing the plurality of metadata labels to determine characteristic features of the element(s) of interest; building a representation of the electronic form based on the plurality of metadata labels; generating a plurality of permutations of the representation of the electronic form by applying a predetermined set of variations to the representation; and training either a classification model, an extraction model, or both using: the representation of the electronic form, and the plurality of permutations of the representation of the electronic form. Corresponding systems and computer program products are also disclosed.
Abstract:
In one embodiment, a method includes receiving a digital image captured by a mobile device; and using a processor of the mobile device: generating a first representation of the digital image, the first representation being characterized by a reduced resolution; generating a first feature vector based on the first representation; comparing the first feature vector to a plurality of reference feature matrices; classifying an object depicted in the digital image as a member of a particular object class based at least in part on the comparing; and determining one or more object features of the object based at least in part on the particular object class. Corresponding systems and computer program products are also disclosed.
Abstract:
Systems, methods, and computer program products are disclosed for performing workflows using a mobile device, without requiring tactile input from the user. The workflow is thus “touchless” and may utilize input preferably including optical data and/or audio data. Tactile input may be optionally provided in some embodiments, but the workflow is configured to be performed without any tactile input. Accordingly, in one embodiment, a computer-implemented method for performing a touchless mobile workflow includes: invoking a mobile application using a mobile device; receiving auditory input via the mobile device; and performing a business workflow via the mobile application based on the auditory input. Corresponding systems and computer program product embodiments configured for touchless mobile workflows are also described.
Abstract:
In various embodiments, methods, systems, and computer program products for determining distance between an object and a capture device are disclosed. The distance determination techniques are based on image data captured by the capture device, where the image data represent the object. These techniques improve the function of capture devices such as mobile phones by enabling determination of distance using a single lens capture device, and based on intrinsic parameters of the capture device, such as focal length and scaling factor(s), in preferred approaches. In some approaches, the distance estimation may be based in part on a priori knowledge regarding size of the object represented in the image data. Distance determination may be based on a homography transform and/or reference image data representing the object, a same type or similar type of object, in more approaches.
Abstract:
A method includes: receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; analyzing the ID based at least in part on the ID classification; determining at least some identifying information from the ID; at least one of building an ID profile and updating the ID profile, based at least in part on the analysis; providing at least one of the ID and the ID classification to a loan application workflow and/or a new financial account workflow; and driving at least a portion of the workflow based at least in part on the ID and the ID classification. Corresponding systems and computer program products are also disclosed.
Abstract:
In one approach, a method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting data of interest from the image based at least in part on the OCR; and validating the extracted data of interest against reference information stored on the mobile device. In another embodiment, a method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting data of interest from the image based at least in part on the OCR; and validating authenticity of the document based on comparing some or all of the extracted data of interest to reference information stored on the mobile device.
Abstract:
According to one embodiment, a system includes a processor and logic in and/or executable by the processor to cause the processor to: initiate a capture operation using an image capture component of the mobile device, the capture operation comprising; capturing video data; and estimating a plurality of motion vectors corresponding to motion of the image capture component during the capture operation; detect a document depicted in the video data; track a position of the detected document throughout the video data; select a plurality of images using the image capture component of the mobile device, wherein the selection is based at least in part on: the tracked position of the detected document; and the estimated motion vectors; and generate a composite image based on at least some of the selected plurality of images.
Abstract:
In one embodiment, a system includes: a processor; and logic in and/or executable by the processor to cause the processor to: generate a first feature vector based on a digital image captured by a mobile device; compare the first feature vector to a plurality of reference feature matrices; classify an object depicted in the digital image as a member of a particular object class based at least in part on the comparison; determine one or more object features of the object based at least in part on the particular object class; and detect one or more additional objects belonging to the particular object class based on the determined object feature(s). The one or more additional objects are depicted either in the digital image or another digital image received by the mobile device. Corresponding computer program products are also disclosed.
Abstract:
In one approach, a method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting data of interest from the image based at least in part on the OCR; and validating the extracted data of interest against reference information stored on the mobile device. In another embodiment, a method includes: capturing an image of a document using a camera of a mobile device; performing optical character recognition (OCR) on the image of the document; extracting data of interest from the image based at least in part on the OCR; and validating authenticity of the document based on comparing some or all of the extracted data of interest to reference information stored on the mobile device.
Abstract:
In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. Myriad features enable and/or facilitate processing of such digital images using a mobile device that would otherwise be technically impossible or impractical, and furthermore address unique challenges presented by images captured using a camera rather than a traditional flat-bed scanner, paper-feed scanner or multifunction peripheral.