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.

Systems and methods for mobile image capture and processing

A method according to one embodiment includes extracting an identifier from an electronic first document, and identifying a complementary document associated with the first document using the identifier. A validity of the first document is determined by simultaneously considering: textual information from the first document; textual information from the complementary document; and predefined business rules. An indication of the determined validity is output. Systems and computer program products for providing, performing, and/or enabling the methodology presented above are also presented.

Systems, methods, and computer program products for determining document validity

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.

Systems and methods for classifying objects in digital images captured using mobile devices

A method includes receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; building an extraction model based on the ID classification; extracting data from the ID based on the extraction model; building an ID profile based on the extracted data; storing the ID profile to a memory of the mobile device; detecting a predetermined stimulus in a workflow; identifying workflow-relevant data in the stored ID profile at least partially in response to detecting the predetermined stimulus; providing the workflow-relevant data from the stored ID profile to the workflow; and driving at least a portion of the workflow using the workflow-relevant data. Related systems and computer program products are also disclosed.

Systems and methods for identification document processing and business workflow integration

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. The preferred processing settings and attributes are determined interactively in real time as well as non real time, automatically and a combination thereof.

Systems and methods of processing scanned data

A disjoint graph structure for packet classification in communication systems is presented. The disjoint graph is comprised of two types of data structures; an elementary interval tree (EIT) and a disjoint interval tree (DIT). The disjoint graph is constructed based on a range-specified rule set finding particular application in the classification of data packets. Each rule in the rule set has an equal number of fields and each field specifies a range referred to as an integer interval having a lower and an upper bound. The disjoint graph has the same number of layers as there are fields in each rule. The layers are comprised of nodes, and each node has an associated rule set selected from the range-specified rule set. The disjoint graph enables packet classification in only one pass through the tree. The EIT and DIT structures are also presented in detail.

Yun Zhang

Papers

Data structure for range-specified algorithms