Abstract: Techniques for capturing long document images and generating composite images therefrom include: detecting a document depicted in image data; tracking a position of the detected document within the image data; selecting a plurality of images, wherein the selection is based at least in part on the tracked position of the detected document; and generating a composite image based on at least one of the selected plurality of images. The tracking and selection are optionally but preferably based in whole or in part on motion vectors estimated at least partially based on analyzing image data such as test and reference frames within the captured video data/images. 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: A method includes: displaying a digital image on a first portion of a display of a mobile device; receiving user feedback via the display of the mobile device; analyzing the user feedback to determine a meaning of the user feedback; based on the determined meaning of the user feedback, analyzing a portion of the digital image corresponding to either the point of interest or the region of interest to detect one or more connected components depicted within the portion of the digital image; classifying each detected connected component depicted within the portion of the digital image; estimating an identity of each detected connected component based on the classification of the detected connected component; and one or more of: displaying the identity of each detected connected component on a second portion of the display of the mobile device; and providing the identity of each detected connected component to a workflow.

Abstract: Systems, methods, and computer program products for smart, automated capture of textual information using optical sensors of a mobile device are disclosed. The capture and provision is context-aware, and determines context of the optical input, and invokes a contextually-appropriate workflow based thereon. The techniques also provide capability to normalize, correct, and/or validate the captured optical input and provide the corrected, normalized, validated, etc. information to the contextually-appropriate workflow. Other information necessary by the workflow and available to the mobile device optical sensors may also be captured and provided, in a single automatic process. As a result, the overall process of capturing information from optical input using a mobile device, invoking an appropriate workflow, and providing captured information to the workflow is significantly simplified and improved in terms of accuracy of data transfer/entry, speed and efficiency of workflows, and user experience.

Abstract: Computer program products include program code readable/executable by one or more processors, and configured to cause the processor(s) to: receive an image of a part or all of a document selected from a group consisting of: a gift card, an invoice, a bill, a receipt, a sales order, an insurance claim, a medical insurance document, and a benefits document; perform optical character recognition (OCR) on the image; extract at least a partial address of a sender of the document; compare the at least partial address of the sender to a plurality of addresses in a first database; and identify one or more of: textual information specific to the sender; and data formatting specific to the sender. The code configured to cause the processor to receive the image, perform the OCR, extract and compare the (at least partial) address, and identify sender-specific information is preferably a processor of a mobile device.

Abstract: Systems, methods, and computer program products are disclosed and include: initiating 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. The systems, techniques, and computer program products also include detecting a document depicted in the video data; tracking a position of the detected document throughout the video data; selecting 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 generating a composite image based on at least some of the selected plurality of images.

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 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; and classifying an object depicted in the digital image as a member of a particular object class based at least in part on the comparing.

Abstract: Systems, methods, and computer program products for smart, automated capture of textual information using optical sensors of a mobile device are disclosed. The textual information is provided to a mobile application or workflow without requiring the user to manually enter or transfer the data without requiring user intervention such as a copy/paste operation. The capture and provision context-aware, and can normalize or validate the captured textual information prior to entry in the workflow or mobile application. Other information necessary by the workflow and available to the mobile device optical sensors may also be captured and provided, in a single automatic process. As a result, the overall process of capturing information from optical input using a mobile device is significantly simplified and improved in terms of accuracy of data transfer/entry, speed and efficiency of workflows, and user experience.

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.

Abstract: In various embodiments, methods, systems, and computer program products for detecting, estimating, calculating, etc. characteristics of a document based on reference objects depicted on the document are disclosed. In one approach, a computer-implemented method for processing a digital image depicting a document includes analyzing the digital image to determine one or more of a presence and a location of one or more reference objects; determining one or more geometric characteristics of at least one of the reference objects; defining one or more region(s) of interest based at least in part on one or more of the determined geometric characteristics; and detecting a presence or an absence of an edge of the document within each defined region of interest. Additional embodiments leverage the type of document depicted in the image, multiple frames of image data, and/or calculate or extrapolate document edges rather than locating edges in the image.

Abstract: Systems, methods, and computer program products for capturing and analyzing image data, preferably video data, are disclosed. The inventive concepts include using multiple frames of image data to generate a composite image, where the composite image may be characterized by a higher resolution than one or more of the individual frames used to generate the composite image, and/or absence of a blurred region present in one or more of the individual frames. Inventive techniques also include determining a minimum capture resolution appropriate for capturing images of particular objects for downstream processing, and optionally triggering generation of a composite image having sufficient resolution to facilitate the downstream processing in response to detecting one or more frames of image data are characterized by a resolution, and/or a region having a resolution, less than the minimum capture resolution appropriate for capturing images of those particular objects.

Abstract: A method includes receiving or capturing a digital image using a mobile device, and using a processor of the mobile device to: determine whether an object depicted in the digital image belongs to a particular object class among a plurality of object classes; determine one or more object features of the object based at least in part on the particular object class at least partially in response to determining the object belongs to the particular object class; build or select an extraction model based at least in part on the one or more determined object features; and extract data from the digital image using the extraction model. The extraction model excludes, and/or the extraction process does not utilize, optical character recognition (OCR) techniques. Related systems and computer program products are also disclosed.

Abstract: In various embodiments, methods, systems, and computer program products for capturing and processing digital images captured by a mobile device are disclosed. In one embodiment, a method includes capturing image data using a mobile device, the image data depicting a digital representation of a document; defining, based on the image data, a plurality of candidate edge points corresponding to the document; defining four sides of a tetragon based on at least some of the plurality of candidate edge points; determining a plurality of fields within the tetragon; for each field, determining at least a field location and a field data type; associating each determined field location with each field data type to generate a plurality of metadata labels; and associating the plurality of metadata labels with an image of an electronic form.

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 capturing plural frames of video data using a mobile device. The frames are analyzed to determine whether any depict an object exhibiting one or more defining characteristics, and if so, whether those frame(s) depicting the object also satisfy one or more predetermined quality control criteria. If one or more of the frames depict the object and also satisfy the one or more predetermined quality control criteria, the method further includes automatically capturing an image of the object. Exemplary defining characteristics are specified for various types of object, particularly objects comprising documents. Related systems and computer program products are also disclosed. The presently disclosed techniques and systems represent translational developments across the fields of image processing and business process management.

Abstract: An efficient method and system to enhance digital acquisition devices for analog data is presented. The enhancements offered by the method and system are available to the user in local as well as in remote deployments yielding efficiency gains for a large variety of business processes. The quality enhancements of the acquired digital data are achieved efficiently by employing virtual reacquisition. The method of virtual reacquisition renders unnecessary the physical reacquisition of the analog data in case the digital data obtained by the acquisition device are of insufficient quality. The method and system allows multiple users to access the same acquisition device for analog data. In some embodiments, one or more users can virtually reacquire data provided by multiple analog or digital sources. The acquired raw data can be processed by each user according to his personal preferences and/or requirements.

Abstract: A method includes receiving user input defining a workflow comprising one or more activities and one or more rules; receiving user input defining a user interface (UI) configured to facilitate a user performing the workflow at least in part using a processor of a mobile device; and generating a mobile software application based on the workflow and the UI. In another embodiment, a method includes: instantiating a mobile application on a mobile device; launching a workflow within the mobile application, the workflow comprising one or more activities and one or more rules; rendering one or more user interfaces based at least in part on the workflow; displaying at least one of the user interfaces on a display of the mobile device; receiving user input via at least one of the user interfaces; and modifying the workflow based at least partially on user input. Systems and computer program products are also disclosed.

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. Notably, the presently disclosed systems and techniques enable three-dimensional reconstruction of objects depicted in image captured using a camera of a mobile device. The reconstruction corrects or compensates for perspective distortion caused by camera-based capture.

Abstract: Systems, computer program products, and techniques for discriminating hand and machine print from each other, and from signatures, are disclosed and include determining a color depth of an image, the color depth corresponding to at least one of grayscale, bi-tonal and color; reducing color depth of non-bi-tonal images to generate a bi-tonal representation of the image; identifying a set of one or more graphical line candidates in either the bi-tonal image or the bi-tonal representation, the graphical line candidates including one or more of true graphical lines and false positives; discriminating any of the true graphical lines from any of the false positives; removing the true graphical lines from the bi-tonal image or the bi-tonal representation without removing the false positives to generate a component map comprising connected components and excluding graphical lines; and identifying one or more of the connected components in the component map.