Abstract:
Systems, computer program products, and techniques for reconstructing objects depicted in digital image data within a three-dimensional space are disclosed, according to various exemplary embodiments. The inventive concepts uniquely utilize internal features to accomplish reconstruction, thereby avoiding reliance on reconstructing objects based on information derived from location of edges. The inventive concepts thus provide an improvement over conventional object reconstruction since objects may be reconstructed even when edges are obscured or not depicted in the digital image data. In one aspect, a computer-implemented method of reconstructing an object depicted in a digital image includes: detecting a plurality of identifying features of the object, wherein the plurality of identifying features are located internally with respect to the object; and reconstructing the digital image of the object within a three dimensional coordinate space based at least in part on some or all of the plurality of identifying features.
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:
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:
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.
Abstract:
In various embodiments, methods, systems, and computer program products for processing digital images captured by a mobile device are disclosed. The exemplary image processing techniques are coupled with inbound and outbound communications protocols and workflows configured to facilitate closed-loop processing, such that a method includes initiating a workflow; providing one or more of case information and raw data to the workflow; processing one or more of the case information and the raw data to generate a processing result; storing at least some of the case information in association with the processing result, wherein the associated case information acts as an identifier of the processing result; transmitting at least the processing result and the identifier; receiving, in response to the transmitting, a reply comprising the identifier; and retrieving at least the processing result using the identifier.
Abstract:
In one embodiment, a method includes performing optical character recognition (OCR) on an image of a financial document and at least one of: (a) correct OCR errors in the financial document using at least one of textual information from a complementary document and predefined business rules; (b) normalize data from the complementary document using at least one of textual information from the financial document and the predefined business rules; and (c) normalize data from the financial document using at least one of textual information from the complementary document and the predefined business rules. Exemplary systems and computer program products are also disclosed.
Abstract:
A method according to one embodiment includes performing optical character recognition (OCR) on an image of a first document; and at least one of: correcting OCR errors in the first document using at least one of textual information from a complementary document and predefined business rules; normalizing data from the complementary document using at least one of textual information from the first document and the predefined business rules; and normalizing data from the first document using at least one of textual information from the complementary document and the predefined business rules. Additional systems, methods and computer program products are also presented.
Abstract:
A method according to one embodiment includes performing optical character recognition (OCR) on an image of a first document; generating a list of hypotheses mapping the first document to a complementary document using: textual information from the first document, textual information from the complementary document, and predefined business rules; at least one of: correcting OCR errors in the first document, and normalizing data from the complementary document, using at least one of the textual information from the complementary document and the predefined business rules; determining a validity of the first document based on the hypotheses; and outputting an indication of the determined validity. Additional systems, methods and computer program products are also presented.
Abstract:
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.
Abstract:
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.