International Business Machines Corporation

Amir Geva

Mattias Marder

Eugeniusz Walach

Eugene Walach

Shay Ben-David

Tal Drory

David Nahamoo

Hagai Aronowitz

Ron Hoory

Ehud Dov Karnin

Ella Barkan

Jason William Pelecanos

Amnon Ribak

Orith Toledo-Ronen

Ami Ben-Horesh

Yoav Nahshon

Doron Tal

Sivan Harary

Sara Porat

Sivan Gleichman

Rutger Simonsson

Jan Henrik Stromback

A method comprising using at least one hardware processor for: providing a set of development supervectors representing features of biometric samples of multiple subjects, the biometric samples being of at least a first and a second different biometric modalities; providing at least a first and a second enrollment supervectors representing features of at least a first and a second enrollment biometric samples of a target subject correspondingly, wherein the at least first and second enrollment samples are of the at least first and the second different biometric modalities correspondingly; providing at least a first and a second verification supervectors representing features of at least a first and a second verification biometric samples of the target subject correspondingly, wherein the at least first and second verification samples are of the at least first and second different biometric modalities correspondingly; concatenating the development supervectors to a set of development generic supervector, the at least first and second enrollment supervectors to a single enrollment generic supervector and the at least first and second verification supervectors to a single verification generic supervector; and verifying an identity of the target subject based on a fused score calculated for the verification generic supervector, wherein the fused score is calculated based on the enrollment generic supervector and the set of development generic supervectors.

Biometric authentication

A computer-implemented method for automating interaction with a computer system includes linking a control computer system to an input interface and to an output interface of a client computer system, which is operative for producing user interface images on a display device. The control computer system executes distinct software modules that include a virtual operator for simulating actions of a human operator. Execution of the software modules causes the control computer system to capture an image from the output interface, and to recognize information in the image. In response to the information, the virtual operator controls an input device to automatically execute predetermined operations on the client computer system via the input interface.

Automated application interaction using a virtual operator

A method includes identifying, in an image, a shelf, a price tag affixed to the shelf, a first group of one or more first products resting on the shelf and positioned on a first side of the price tag, and a second group of one or more second products resting on the shelf and positioned on a second side of the price tag. One or more first candidates are identified for the one or more first products, and one or more second candidates are identified for the one or more second products. Upon receiving information indicating expected locations for the first and the second candidates, determining, an identity of the first products can be determined based on the expected locations and the one or more first candidates, and an identity of second products can be determined based on the expected locations and the one or more second candidates.

Product identification via image analysis

Systems and methods for extracting text from images rendered on a display screen, the method comprising capturing a color image rendered on a display screen; and transforming the color image to binary color image, preserving text-like graphic components and filtering out non-text-like graphical components. The transforming comprises scanning one or more areas of the color image; and detecting continuous bi-tonal regions in the scanned one or more areas, wherein the continuous bi-tonal regions have large variances.

Text extraction from graphical user interface content

Machines, systems and methods for recognizing visual change in a graphical user interface (GUI) environment, the method comprising determining position of an active GUI object in the GUI environment based on known attributes of the active GUI object; monitoring a focus area in the active GUI object to detect visual changes in attributes of the focus area, without regard to any visual changes outside the focus area; determining whether the active GUI object has moved or has been resized, in response to determining a visual change in the attributes of the focus area; and determining position of a new active GUI object in the GUI environment, in response to determining that the active GUI object has not been moved or has not been resized.

Active and efficient monitoring of a graphical user interface

Machines, systems and methods for enhanced optical character recognition are provided. In one embodiment, the method comprises identifying a sample character in a textual context to be optically recognized; comparing the sample character with a template character, wherein the sample character is scaled into a first grid and the template character is scaled into a second grid; identifying one or more pixels in the sample character within the first grid and one or more pixels in the template character in the second grid, wherein the one or more pixels are identified as belonging to a foreground category in the textual content, a foreground pixel having at least N gradients corresponding to edges of the foreground pixel that are juxtaposed to a neighbor pixel, wherein a contour foreground pixel has at least one gradient that is neighbored by a background pixel in the textual context.

Optical match character classification

Systems and methods for detecting end of a transaction in a computing environment are provided. The method comprises determining a target area in a graphical user environment displayed on a display screen, wherein a change is expected to occur when end of a transaction is reached; masking the target area at least partially to remove content included in the target area that is present before or after the transaction was initiated; monitoring the target area for change in content; and detecting the end of the transaction when the content of the target area has changed.

Recognition techniques to enhance automation in a computing environment

A method, including automatically identifying, by a processor, a region of a digital image containing first pixels, each situated on a positive horizontal gradient, and second pixels in proximity to the first pixels, each situated on a negative horizontal gradient. A distribution of intensities of a color channel is then calculated for the pixels in the region, and the distribution is analyzed in order to detect whether the region contains anti-aliased text.

Detecting anti-aliased text in digital images

A method, system and computer software product are provided for process automation. The method includes monitoring one or more workstations to obtain multiple sets of character and graphical information including user actions, times and durations associated with the user actions, user-entered data, and retrieved character and graphical screen data. The method further includes identifying functional events from the sets, defining focal states as respective historic patterns of the functional events, and generating a set of facilitating scripts associated with respective ones of the focal states. The facilitating scripts each provide one or more automatic actions in the workstations. At least a portion of the set of facilitating scripts are then executed.

Adaptive business process automation

A method and system for automatically classifying an input form field as designed to hold sensitive information. The method may include selecting an input characteristic associated with the input form field. The method may also include classifying the input form field as designed to hold sensitive information by considering classifying information of other input form fields having the same input characteristic. The method may further include statistically determining whether a similar input form field is indicated as designed to hold sensitive information by at least a predetermined threshold value of the other input fields. A computer program product is also disclosed.

Automatically classifying an input from field with respect to sensitivity of information it is designed to hold

A method and system for recognizing a character affected by a noise or an obstruction is disclosed. After receiving an image with characters, a character being affected by a noise or an obstruction is determined. Then, areas in the character where the noise or obstruction affected are precisely located. Templates representing every possible character in the image are updated by removing equivalent areas to the areas in the character being affected by the noise or obstruction. Then, the character is classified in a template among the updated templates by finding the template having the highest number of matching pixels with the character.

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Yokneam, Israel

Amir Geva