Sharp Laboratories of America, Inc

Xinyu Xu

Petrus J L Van Beek

Chang Yuan

Louis Joseph Kerofsky

Miao Liao

Masakazu Yanase

Hao Pan

Xiao-Fan Feng

Hae-Jong Seo

Petrus Van Beek

Xiaofan Feng

Qiang Zhang

Fan Wang

Xiaofeng Fan

Aspects of the present invention are related to methods and systems for vision-based computation of ego-motion.

Methods and systems for vision-based motion estimation

Aspects of the present invention are related to systems and methods for determining local-analysis-window size and weighting parameters in a gradient-based motion estimation system.

Motion estimation in a video sequence

Aspects of the present invention are related to methods and systems for autonomous navigation using visual-landmark recognition. One method may include scanning a captured image to detect a machine-readable marker and extracting encoded data therefrom. The data may include an identifying key usable to access a database to retrieve physical attributes associated with the marker. The method may include using the physical attributes to compute a position and an orientation of a mobile agent relative to a landmark object associated with the marker. The method may further include determining a path toward a next route location based on the position of the next route location and the computed position and orientation of the mobile agent and controlling the mobile agent to drive along the path toward the next route location.

Methods and systems for mobile-agent navigation

Aspects of the present invention are related to methods and systems for autonomous navigation using visual landmark recognition.

Methods and systems for determining data-adaptive weights for motion estimation in a video sequence

A system for image enhancement includes a computer receiving an input image, and modifies the entire range of frequencies of the image, wherein the modifying is greater for the lower frequency aspects of the input image relative to the higher frequency aspects of the input image based upon a brightening process that is based upon a brightening selection, where the brightening selection is based upon a backlight level of a display to display the input image. The computer modifies the higher frequency aspects of the input image based upon an enhancement process that is based upon the brightening selection which is based upon the backlight level of the display. The computer combines the modifies image based upon the brightening process and the modified image based upon the enhancement process.

System for image enhancement

A system for identifying a repair cut location for a defect in a liquid crystal device includes receiving an input image, a defect mask image, and a landmark structure image. The system determines a repair cut location, based upon the input image, the defect mask image, and the landmark structure image, for a liquid crystal device proximate the defect. The determination may be based upon a type of said defect, a cause of said defect, a position of said defect, and a spatial relationship of the defect and a structure of the landmark image.

System for defect detection and repair

A method for classification of samples comprising providing a trained statistical model based upon a set of initial samples. Receiving a set of first samples and training a first statistical model base upon the first set of samples, where the first statistical model is of the same class as the trained statistical model. Receiving a set of second samples and training a second statistical model base upon the second set of samples, where the second statistical model is of the same class as the trained statistical model. The trained statistical model, the first statistical model, and the second statistical model, being independent of each other and collectively used to classify another sample.

Supervised and semi-supervised online boosting algorithm in machine learning framework

Aspects of the present invention are related to systems, methods and apparatus for image-based automatic detection of a defective area in a flat panel display and classification of the defect type and the cause of the detected defect.

Methods, systems and apparatus for defect detection and classification

A system for the identification of feature points in low contrast images.

System for feature detection for low contrast images

A method for image processing includes determining edge pixels of a model image and determining features for the edge pixels of the model image. The image processing includes determining edge pixels of an input image and determining features for the edge pixels of the input image. The system matches the features of the model image with the features of the input image to determine candidate locations of an object within the input image.

Edge based template matching

A computer-implemented method for enhancing an input image that includes modifying the relatively lower frequency aspects of the input image based upon a brightening process, where the brightening process is based upon a brightening selection which is based upon a combination of an under brightening term and a clipping term and a joint saturation boost and brightening. The method modifies the relatively higher frequency aspects of the input image based upon reducing lower amplitude noise and enhancing the noise reduced higher frequency aspects of the input image, and combines the modified relatively lower frequency aspects of the input image and the modified relatively higher frequency aspects of the input image.

A system for detecting newton ring mura on a display includes sensing an image of the display with an image capture device and determining a border boundary of an illuminated portion of the display. The image is spatially filtered as defined by the border boundary using a filter that reduces sensor noise and a grid pattern of the display. The spatially filtered image is processed to determine if a region proximate a pixel location is a potential newton ring mura defect and characterizing the potential newton ring mura defects to remove at least one of the potential newton ring mura defects.

Newton ring mura detection system

A system for image processing includes determining edge pixels of a model image using an edge based technique and determining an angular orientation for each the edge pixels of the model image. The system determines a histogram of gradient orientations based upon the angular orientations of the model image. The system determining edge pixels of an input image using an edge based technique and determining an angular orientation for each of the edge pixels of the input image. The system determines a histogram of gradient orientations based upon the angular orientations of the input image. The system compares the histogram of gradient orientations of the model image with the histogram of gradient orientations of the input image to determine candidate locations of an object within the input image.

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Vancouver, WA, United States of America

Xinyu Xu