The Boeing Company

David Leonard Caballero

Thomas P Weismuller

David K Lee

Amir Leon Liaghati

Thomas Weismuller

Thomas Paul Weismuller

A method for blur correction determines a first constant for a first pixel segment and a second constant for a second pixel segment for each of the multipliers that results in a first mean error for the first pixel segment being and a second mean error for the second pixel segment being within a mean error threshold. A first multiplier is selected from the multipliers with the corresponding first constant for the first pixel segment and second multiplier is selected from the multipliers with the corresponding second constant for the second segment that has the probability of the frames with the measured ranges being within the selected error threshold. A data file comprising the first multiplier, the corresponding first constant for the first multiplier, the second multiplier, and the corresponding second constant for the second multiplier is created for a platform computer system for a platform.

Blur correction system

Embodiments herein describe tracking the location and orientation of a target in a digital image. In an embodiment, this tracking can be used to control navigation for a vehicle. In an embodiment, a digital image can be captured by a visual sensor is received. A first array including a plurality of binary values related to the pixel velocity of a first plurality of pixels in the digital image as compared to corresponding pixels in a first one or more prior digital images can be generated. A second array including a plurality of values related to the standard deviation of pixel intensity of the first plurality of pixels in the digital image as compared to corresponding pixels in a second one or more prior digital images can be further generated. A plurality of thresholds relating to the values in the second array can be determined. A plurality of target pixels and a plurality of background pixels can be identified in the digital image, based on the first array, the second array, and the plurality of thresholds. A binary image related to the digital image, based on the identified plurality of target pixels and the identified plurality of background pixels, and identifying at least one of a location and an orientation of the target in the digital image based on the binary image, can be generated. In an embodiment, a command can be transmitted to a navigation system for a vehicle, to assist in navigating the vehicle toward the target, based on the identified at least one of a location and an orientation of the target.

Cluttered background removal from imagery for object detection

A method and apparatus for resolving a set of objects in an image of an area. A partition that captures a set of objects is identified using the image. The partition is comprised of a group of contiguous object pixels. A number of local max pixels are identified from the group of contiguous object pixels in the partition. A quantitative resolution of the set of objects captured in the partition is performed based on the number of local max pixels identified.

Resolving closely spaced objects

A computer-implemented method and apparatus for detecting an object of interest. An edge image is generated from an image of a scene. A sectioned structure comprising a plurality of sections is generated for use in analyzing the edge image. The edge image is analyzed using the sectioned structure to detect a presence of the object of interest in the edge image.

Isotropic feature matching

A method of navigating a space vehicle. An image of a planet surface is received. The received image is processed to identify edge pixels and angle data. The edge pixels and angle data are used to identify planetary features by shape, size, and spacing relative to other planetary features. At least some of the planetary features are compared with a predefined planet surface description including sizes and locations of planet landmarks. One or more matches are determined between the planetary feature(s) and the planet surface description. Based on the match(es), a location of the space vehicle relative to the planet is determined.

Methods and apparatus for planetary navigation

A method and system for increasing the certainty of a silhouette matching process, where the process is being used for attitude determination of an object of interest, for example an aircraft. The method involves using one or more mask images that include structure or features that may or may not always be associated with the object of interest, and overlaying the mask image(s) onto a library image of the aircraft. Each pixel of the library image is compared against corresponding pixels of the mask image(s) to determine which pixels represent ambiguous areas of the library image. Those pixels are eliminated from consideration in determining a Fit score, where the Fit score represents a percentage value indicative of a certainty of the matching process in identifying the attitude of the aircraft. The method and system is applicable to a wide ranging variety of object detection applications.

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Huntington Beach, CA, United States of America

David Leonard Caballero