Abstract: Capturing information from an imprinted item comprises a computing device that receives an image of a back side of an imprinted item, the payment instrument comprising information imprinted thereon such that the imprinted information protrudes from a front side of the imprinted item and the imprinted information is indented into the back side of the imprinted item. The computing device extracts sets of characters from the image of the back side of the imprinted item based on the imprinted information indented into the back side of the imprinted item and depicted in the image of the back side of the imprinted item. The computing device applies a first character recognition application to process the sets of characters extracted from the image of the back side of the imprinted item and categorizes each of the sets of characters into one of a plurality of categories relating to the information.

Abstract: Capturing information from an imprinted item comprises a computing device that receives an image of a back side of an imprinted item, the payment instrument comprising information imprinted thereon such that the imprinted information protrudes from a front side of the imprinted item and the imprinted information is indented into the back side of the imprinted item. The computing device extracts sets of characters from the image of the back side of the imprinted item based on the imprinted information indented into the back side of the imprinted item and depicted in the image of the back side of the imprinted item. The computing device applies a first character recognition application to process the sets of characters extracted from the image of the back side of the imprinted item and categorizes each of the sets of characters into one of a plurality of categories relating to the information.

Abstract: Capturing information from an imprinted item comprises a computing device that receives an image of a back side of an imprinted item, the payment instrument comprising information imprinted thereon such that the imprinted information protrudes from a front side of the imprinted item and the imprinted information is indented into the back side of the imprinted item. The computing device extracts sets of characters from the image of the back side of the imprinted item based on the imprinted information indented into the back side of the imprinted item and depicted in the image of the back side of the imprinted item. The computing device applies a first character recognition application to process the sets of characters extracted from the image of the back side of the imprinted item and categorizes each of the sets of characters into one of a plurality of categories relating to the information.

Abstract: Capturing information from an imprinted item comprises a computing device that receives an image of a back side of an imprinted item, the payment instrument comprising information imprinted thereon such that the imprinted information protrudes from a front side of the imprinted item and the imprinted information is indented into the back side of the imprinted item. The computing device extracts sets of characters from the image of the back side of the imprinted item based on the imprinted information indented into the back side of the imprinted item and depicted in the image of the back side of the imprinted item. The computing device applies a first character recognition application to process the sets of characters extracted from the image of the back side of the imprinted item and categorizes each of the sets of characters into one of a plurality of categories relating to the information.

Abstract: Methods and systems for grapheme splitting of text input for recognition are provided. A method may include receiving a text input in a script and segmenting the text input into one or more graphemes. Each of the one or more graphemes may be split into one or more recognition units based on one or more recognition unit identification criteria associated with the script. Next, a text recognition system may be trained using the recognition units. Text input may be handwritten text input received from a user or a scanned image of text.

Abstract: Capturing information from payment instruments comprises receiving, using one or more computer devices, an image of a back side of a payment instrument, the payment instrument comprising information imprinted thereon such that the imprinted information protrudes from a front side of the payment instrument and the imprinted information is indented into the back side of the payment instrument; extracting sets of characters from the image of the back side of the payment instrument based on the imprinted information indented into the back side of the payment instrument and depicted in the image of the back side of the payment instrument; applying a first character recognition application to process the sets of characters extracted from the image of the back side of the payment instrument; and categorizing each of the sets of characters into one of a plurality of categories relating to information required to conduct a payment transaction.

Abstract: Capturing information from payment instruments comprises receiving, using one or more computer devices, an image of a back side of a payment instrument, the payment instrument comprising information imprinted thereon such that the imprinted information protrudes from a front side of the payment instrument and the imprinted information is indented into the back side of the payment instrument; extracting sets of characters from the image of the back side of the payment instrument based on the imprinted information indented into the back side of the payment instrument and depicted in the image of the back side of the payment instrument; applying a first character recognition application to process the sets of characters extracted from the image of the back side of the payment instrument; and categorizing each of the sets of characters into one of a plurality of categories relating to information required to conduct a payment transaction.

Abstract: Methods and systems for grapheme splitting of text input for recognition are provided. A method may include receiving a text input in a script and segmenting the text input into one or more graphemes. Each of the one or more graphemes may be split into one or more recognition units based on one or more recognition unit identification criteria associated with the script. Next, a text recognition system may be trained using the recognition units. Text input may be handwritten text input received from a user or a scanned image of text.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing optical character recognition. In one aspect, a method includes receiving a text image I. A set of feature functions are evaluated for a log linear model to determine respective feature values for the text image I, wherein each feature function hi maps the text image I to a feature value, and wherein each feature function hi is associated with a respective feature weight ?i. A transcription {circumflex over (T)} is determined that minimizes a cost of the log linear model.

Abstract: Capturing information from payment instruments comprises receiving, using one or more computer devices, an image of a back side of a payment instrument, the payment instrument comprising information imprinted thereon such that the imprinted information protrudes from a front side of the payment instrument and the imprinted information is indented into the back side of the payment instrument; extracting sets of characters from the image of the back side of the payment instrument based on the imprinted information indented into the back side of the payment instrument and depicted in the image of the back side of the payment instrument; applying a first character recognition application to process the sets of characters extracted from the image of the back side of the payment instrument; and categorizing each of the sets of characters into one of a plurality of categories relating to information required to conduct a payment transaction.

Abstract: Methods, systems, and articles of manufacture consistent with certain principles related to the present invention enable a computing system to perform hierarchical topical clustering of text data based on statistical modeling of co-occurrences of (document, word) pairs. The computing system may be configured to receive a collection of documents, each document including a plurality of words, and perform a modified deterministic annealing Expectation-Maximization (EM) process on the collection to produce a softly assigned hierarchy of nodes. The process may involve assigning documents and document fragments to multiple nodes in the hierarchy based on words included in the documents, such that a document may be assigned to any ancestor node included in the hierarchy, thus eliminating the hard assignment of documents in the hierarchy.

Abstract: Methods, systems, and articles of manufacture consistent with certain principles related to the present invention enable a computing system to perform hierarchical topical clustering of text data based on statistical modeling of co-occurrences of (document, word) pairs. The computing system may be configured to receive a collection of documents, each document including a plurality of words, and perform a modified deterministic annealing Expectation-Maximization (EM) process on the collection to produce a softly assigned hierarchy of nodes. The process may involve assigning documents and document fragments to multiple nodes in the hierarchy based on words included in the documents, such that a document may be assigned to any ancestor node included in the hierarchy, thus eliminating the hard assignment of documents in the hierarchy.