Morphological automatic triangle orientation detection
Inventors
Pinkus, Alan R • Dommett, David W • Task, Harry Lee
Assignees
United States Department of the Air Force
Publication Number
US-9679216-B2
Publication Date
2017-06-13
Expiration Date
2036-05-05
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Abstract
A system and method are provided for assessing a resolution of an optical sensor. An image is obtained from the optical sensor. A target area is selected from the image. The selected area is subjected to a thresholding process to generate a binary image. Pixels at a center of the binary image are tagged. The remaining pixels of the binary image are looped through, where pixels that are not already tagged, are touching a tagged pixel, and are of the same color of previously tagged pixels are tagged. A plurality of distances associated with each corner of the binary image is calculated from the corner to the nearest tagged pixel in a row or column of pixels. At least two shortest distances of the calculated plurality of distances are selected to determine an orientation of an object defined by the tagged pixels in the generated binary image.
Core Innovation
The invention provides a system, method, and program product for assessing the resolution of an optical sensor by automatically detecting the orientation of triangle targets in digital images obtained from the sensor. The approach uses a morphological automatic triangle orientation detection algorithm which involves obtaining an image from the optical sensor, selecting a target area, thresholding the selected area to create a binary image, tagging center pixels, expanding tagging to connected pixels of the same color, calculating distances from image corners to nearest tagged pixels, and determining the object's orientation based on shortest distances. This method assists in automatic assessment of digital quality and sensor resolution without the need for human observers, aiming to replicate frequency of seeing functions observed in human visual performance.
The problem being solved addresses the challenges in assessing image quality and sensor resolution traditionally reliant on human observers and psychophysical testing, which are laborious, costly, and variable due to observer differences and environmental conditions. Existing methods often rely on subjective quality assessments or target detection algorithm performance measures, which may not accurately reflect human visual performance improvement from image enhancement. The invention fills the need for a computationally efficient, accurate, and automated method to assess sensor resolution and image quality, particularly for complex multi-spectral and fused sensor images, thereby removing the dependency on human observer testing in visual acuity and resolution assessments.
Claims Coverage
The patent includes several independent claims covering a method, a system, and a program product for assessing optical sensor resolution using morphological automatic triangle orientation detection.
Method for resolution assessment using morphological triangle orientation detection
A method comprising obtaining an image from an optical sensor; selecting a target area; thresholding to generate a binary image; tagging pixels at the image center; iteratively tagging adjacent pixels of the same color touching tagged pixels; calculating distances from each binary image corner to the nearest tagged pixel in rows or columns; selecting at least two shortest distances; and determining the orientation of the object defined by the tagged pixels based on the selected distances.
Comparison and quality assessment based on orientation
Comparing the determined orientation to a known orientation and using this comparison to assess the quality of the optical sensor.
Noise elimination in binary image processing
Eliminating noise pixels near the object in the binary image after thresholding to improve the accuracy of orientation detection.
Removal of untagged pixels matching tagged pixel color
Removing pixels that have the same color as tagged pixels but are not tagged before calculating the distances from image corners, to refine the target object representation.
System comprising an optical sensor and a processing unit
A system including an optical sensor, memory, a processor, and program code configured to perform the method steps of image acquisition, target area selection, binary image thresholding, pixel tagging, distance calculation, selection of shortest distances, and orientation determination.
Program product embodying the method steps
A non-transitory computer readable medium storing program code which, when executed, performs image acquisition, target area selection, thresholding, pixel tagging, distance calculations from corners, selection of shortest distances, and orientation determination to assess optical sensor resolution.
Overall, the claims cover an automated, morphological approach to determining the orientation of triangle targets in images from optical sensors by thresholding, pixel tagging, distance measurement from image corners, and orientation determination, which supports sensor resolution and quality assessment without human observers.
Stated Advantages
The approach is computationally efficient and more accurate than contemporary methods.
It automates resolution and quality assessments that traditionally require costly and labor-intensive psychophysical testing with human observers.
Embodiments provide real-time evaluation of various sensors, including visible, infrared, thermal, and synthetic fused sensors, correlating with human visual perception metrics.
Documented Applications
Assessment of image quality and resolution of optical sensors, including visible, near infrared, short-wave infrared, thermal, and synthetic sensors combining multiple sensors.
Automatic resolution assessment of digital imagery from multi-spectral imaging systems and image fusion algorithms.
Replacing human observer-based psychophysical testing methods for visual acuity and resolution.
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