Xerox Corporation

Conduent Business Services, LLC

Other

The Penn State Research Foundation

Zhigang Fan

Shen-Ge Wang

Reiner Eschbach

Yao Rong Wang

Hengzhou Ding

Raja Bala

Lalit Keshav Mestha

Yonghui Zhao

William A Fuss

Aaron Michael Burry

Robert P Loce

Francis Kapo Tse

Alvaro Enrique Gil

Ying-wei Lin

Vishal Monga

Martin Sidney Maltz

Jeng-nan Shiau

Stuart Alan Schweid

Ramesh Nagarajan

Hui Ting Cheng

Vladimir Kozitsky

Emil Victor Rainero

Judith E Stinehour

Frederick J Roberts, Jr

Edgar A Bernal

Jan Philip Allebach

Charles Addison Bouman

Robert S Cooperman

Robert Shuchatowitz

Orhan Bulan

Ricardo L De Queiroz

Claude Fillion

John W Wu

Wencheng Wu

John C Handley

Gaurav Sharma

Yingjun Bai

Michael Robert Campanelli

Saurabh Prabhat

Graham Stephen Pennington

Robert Eero Nuuja

Shriram V Revankar

James R Low

R Victor Klassen

Edward Neil Chapman

Dennis Lee Venable

Martin Edward Banton

Paul Roberts Conlon

Martin Edward Hoover

David E Rumph

Yeqing Zhang

Abu Saeed Islam

Amal Z Malik

Michael Branciforte

Lee Coy Moore

Timothy Wayne Jacobs

David Preston Cummins

Raymond J Clark

Helen HaeKyung Shin

Keith T Knox

Raphael F Bov, Jr

Zhen He

Elizabeth Dubiel Wayman

Yadong Mu

Bingfeng Zhou

David Allen Mantell

Steven Jay Harrington

Linn C Hoover

Beilei Xu

Peter Paul

Edul N Dalal

Jiebo Luo

Michael E Farrell

William J Nowak

Gavan Leonard Tredoux

Robert Alan Clark

Peter J Zehler

Robert John Rolleston

Michael Robert Furst

Thyagarajan Balasubramanian

Michael D Borton

Roger Lee Triplett

Karen Marie Braun

Zhenhuan Wen

Premkumar Rajendran

Tonya L Love

Phillip J Emmett

Norman W Zeck

Tao He

Trac D Tran

William Joseph Hannaway

Farzin Blurfrushan

Reuven J Sherwin

Hao Wu

Matthew Darst

John Christopher Cassidy

Jose Antonio Rodriguez-Serrano

Gerald A Wedekind

Matthew Frederick Hoffmann

Geoffrey John Woolfe

A method for detecting a double-parked vehicle includes identifying a parking region in video data received from an image capture device monitoring the parking region. The method includes defining an enforcement region at least partially surrounding the parking region. The method includes detecting a stationary vehicle in the enforcement region. The method includes determining the occurrence of an event relative to the stationary vehicle. In response to the determined occurrence of the event, the method includes classifying the stationary vehicle as being one of double parked and not double parked.

Video-based system for automated detection of double parking violations

A method of color image processing for quantizing output includes obtaining an input for an object pixel which is represented by a vector in a first color space. A modified input equal to the input plus a sum of errors from other pixels in a neighborhood of the object pixel is generated. For each color component in the first color space, where corresponding color components of the modified input are located with respect to a preset range is determined. If the modified input's color component is greater than the preset range, then that color component for an output is determined to be on; if less than the preset range, then that color component for the output is determine to be off; and, if within the preset range, then that color component for the output is determined to be unknown. A transformed modified input is mapped to a perceptual color space when any color component of the output is unknown. Colors consistent with color components of the output that have already been determined are also mapped to the perceptual color space. The color in the perceptual color space that lies closest to the transformed modified input is chosen. An output in the first color space having color components on and off is generated consistent with the determinations and/or choices made. Error for the object pixel is then calculated as the difference between the output and the modified input.

Reducing smear and slow response artifacts in vector error diffusion

A method, system, and computer-usable tangible storage device for robustly cropping and accurately recognizing license plates to account for noise sources and interfering artifacts are disclosed. License plate images and sub-images can be tightly cropped utilizing an image-based classifier and gradient-based cropping. An image-based classifier can identify the location of valid characters within the image. Because of a number of noise sources, such as, for example, residual plate rotation and shear in the characters within the image, the image-based classifier performs a 'rough' identification of the image boundaries. An additional processing step utilizing gradient-based cropping is performed to fine-tune the license plate image boundaries. Gradient-based cropping eliminates unwanted border artifacts that could substantially impact the segmentation and license plate character recognition results.

Robust cropping of license plate images

As set forth herein, systems and methods are described that facilitate to analyze a video stream from a camera mounted on the side of a school bus, wherein a sub-set of video sequences showing cars illegally passing the stopped school bus are automatically identified through image and/or video processing. The described systems and methods provide a significant savings in terms of the amount of manual review that is required to identify such violations. The video sequences also can be analyzed further to additionally produce images of the license plate (for identification of the violator), thereby providing further reduction in required human processing and review time. In one embodiment, automatic license plate recognition (ALPR) is employed to identify text on the violator's license plate, as well as the state by which the license plate was issued, without requiring human review of the license plate image.

Automated processing method for bus crossing enforcement

A method and system for detecting anomalies in video footage. A training dictionary can be configured to include a number of event classes, wherein events among the event classes can be defined with respect to n-dimensional feature vectors. One or more nonlinear kernel function can be defined, which transform the n-dimensional feature vectors into a higher dimensional feature space. One or more test events can then be received within an input video sequence of the video footage. Thereafter, a determination can be made if the test event(s) is anomalous by applying a sparse reconstruction with respect to the training dictionary in the higher dimensional feature space induced by the nonlinear kernel function.

Anomaly detection using a kernel-based sparse reconstruction model

This disclosure provides a method and system for navigating hard copies of web pages. According to one exemplary method, a hard copy of a web page is navigated by capturing with a mobile device an image of the hard copy, performing OCR on the captured image to identify the captured web page, accessing a database to retrieve a copy of the identified web page and displaying the retrieved copy of the identified web page along with active web page links on the mobile device.

Method and system for navigating a hard copy of a web page

A computer-based apparatus for labeling medications, including: a processor for a computer configured to: calculate a configuration of a first medication package using a first digital image of the first medication package; create, using the configuration, a package template; receive first prescription information including a name of a patient, a name of a medication, a dosage of the medication, an amount of the medication, and a schedule for taking the medication; create a first custom label, using the package template and the first prescription information, the first custom label including a first plurality of data fields including the first prescription information and a configuration for the first custom label; and transmit first data, including the first custom label with the first prescription information entered in the first plurality of data fields, to a printer.

Apparatus, system, and method for personalized medication labels

A mobile electronic device is used to decode a printed correlation mark. The device receives an image of a printed correlation mark, identifies a decoding template, applies the template to detect hidden content within the printed correlation mark, and outputs an image of the detected hidden content on the display. The device may enhance the image before presenting it on the display.

Method and system for visualizing a correlation mark using an electronic device

A method and system for determining one or more dimension estimations for a vehicle. A sequence of image frames of a vehicle is received, and a digital representation of the vehicle is extracted from each image in the sequence of image frames. A bounding box is determined for the vehicle based upon the extracted digital representation for each digital representation of the vehicle and at least one dimension of the vehicle is estimated based upon the determined bounding box. An indication of the at least one estimated dimension is output. The indication of at least one estimated dimension is transferred as an input to a comparison technique for further processing the indication of the at least one estimated dimension. The comparison technique can include a parking determination process configured to determine a recommended spot for the vehicle based upon the indication of the at least one estimated dimension.

Vehicle dimension estimation from vehicle images

A method and a system for automating parking payment includes receiving video data in a sequence of frames provided by a video capture device observing a parking area. The method includes detecting a vehicle in the parking area using the video data. The method further includes receiving information of a vehicle in the parking area provided by a user device. The method includes comparing the characteristics of the detected vehicle with the information from the user device. In response to the characteristics of the detected vehicle being a match to the information sent from the user device, the method includes tracking the detected vehicle across the sequence of frames. The method includes computing a duration that the detected vehicle remains stationary using the tracking. The method includes computing an amount for charging the associated user device based on the duration.

Smartphone augmented video-based on-street parking management system

Methods, systems and processor-readable media for identifying a vehicle for street parking management. An initial identification of one or more vehicles detected parked along a street can be generated based on one or more of a group of factors. The initial identification can be communicated to a user of the vehicle by transmitting an image indicative of the vehicle parked along the street (e.g., via a mobile communications device). An operation can then be implemented for requesting a confirmation or a non-confirmation as to whether the vehicle detected and displayed on the image is associated with the user. Upon confirmation, an operation can be implemented for identifying the at least one vehicle as the initial identification. Upon non-confirmation, an operation can be implemented to query to identify the vehicle associated with the user from among a group of vehicles displayed via the image.

On-street parking management methods and systems for identifying a vehicle via a camera and mobile communications devices

Methods and systems for detecting anomalies in transportation related video footage. In an offline training phase, receiving video footage of a traffic location can be received. Also, in an offline training phase, event encodings can be extracted from the video footage and collected or compiled into a training dictionary. One or more input video sequences captured at the traffic location or a similar traffic location can be received in an online detection phase. Then, an event encoding corresponding to the input video sequence can be extracted. The event encoding can be reconstructed with a low rank sparsity prior model applied with respect to the training dictionary. The reconstruction error between actual and reconstructed event encodings can then be computed in order to determine if an event thereof is anomalous by comparing the reconstruction error with a threshold.

Detecting multi-object anomalies utilizing a low rank sparsity model

A method and system for on-street vehicle parking occupancy estimation via curb detection comprises training a computer system to identify a curb, evaluating image data of the region of interest to determine a region wherein a curb is visible in said region of interest, and estimating a parking occupancy of said region of interest according to said region where said curb is visible.

On-street vehicle parking occupancy estimation via curb detection

This disclosure provides methods and systems of embedding and extracting information in a printed document. According to one exemplary embodiment, a method is provided wherein information is encoded by one or more partial or complete gaps in a line associated with a form, and the line gaps are patterned to provide N-bit codes.

Embedding information in paper forms

This disclosure provides a method, system and computer program product for denoising an image by extending a Block Matching and 3D Filtering algorithm to include decomposition of high contrast image blocks into multiple layers that are collaboratively filtered. According to an exemplary method, the high contrast image blocks are decomposed into a top layer, a bottom layer and a mask layer.

Multiple layer block matching method and system for image denoising

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Webster, NY, United States of America

Zhigang Fan