Target detection method and system
First Claim
1. A method for detecting targets within an image comprising:
- receiving image data;
applying a gradient operator to determine gradient magnitude and direction of the pixels of said image data to produce gradient image data;
skeletonizing the gradient image data to remove unnecessary detail to produce skeletonized image data representing the image primarily by the edges of the objects contained therein;
applying atmospheric compensation to said gradient image data to adjust the skeletonized image data magnitudes in relationship to range;
defining at least one target size box related to the expected target size in the image data;
establishing a gradient threshold level under which the image data is determined to be unrelated to a target edge;
thresholding the skeletonized image data by comparing the skeletonized image data magnitudes to said gradient threshold and producing simplified image data representative of edges of image elements when said skeletonized image data magnitude exceeds said gradient threshold determined in said step of establishing; and
identifying candidate targets within said skeletonized image data by examining the number of different edge directions within the data defined by the target box size surrounding each pixel of each image data element of said simplified image data based on the number of directions of edge image data present in a region of said image.
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Accused Products
Abstract
A method and system detects candidate targets or objects from a viewed scene by simplifying the data, converting the data to gradient magnitude and direction data which is thresholded to simplify the data. Horizontal edges within the data are softened to reduce their masking of adjacent non-horizontal features. One or more target boxes are stepped across the image data and the number of directions of gradient direction data within the box is used to determine the presence of a target. Atmospheric attenuation is compensated. The thresholding used in one embodiment compares the gradient magnitude data to a localized threshold calculated from the local variance of the image gradient magnitude data. Imagery subsets are containing the candidate targets may then be used to detect and identify features and apply a classifier function to screen candidate detections and determine a likely target.
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Citations
82 Claims
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1. A method for detecting targets within an image comprising:
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receiving image data;
applying a gradient operator to determine gradient magnitude and direction of the pixels of said image data to produce gradient image data;
skeletonizing the gradient image data to remove unnecessary detail to produce skeletonized image data representing the image primarily by the edges of the objects contained therein;
applying atmospheric compensation to said gradient image data to adjust the skeletonized image data magnitudes in relationship to range;
defining at least one target size box related to the expected target size in the image data;
establishing a gradient threshold level under which the image data is determined to be unrelated to a target edge;
thresholding the skeletonized image data by comparing the skeletonized image data magnitudes to said gradient threshold and producing simplified image data representative of edges of image elements when said skeletonized image data magnitude exceeds said gradient threshold determined in said step of establishing; and
identifying candidate targets within said skeletonized image data by examining the number of different edge directions within the data defined by the target box size surrounding each pixel of each image data element of said simplified image data based on the number of directions of edge image data present in a region of said image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A system for detecting targets within an image from image data supplied thereto comprising:
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a gradient processor applying a gradient operator to determine gradient magnitude and direction of the pixels of said image data to produce gradient image data;
a skeletonizer removing unnecessary detail from the gradient image data to produce skeletonized image data representing the image primarily by the edges of the objects contained therein;
atmospheric compensator compensating for range related atmospheric attenuation in said gradient image data by adjusting the skeletonized image data magnitudes in an amount related to range;
a thresholder eliminating data that falls below a predetermined threshold within the skeletonized image data by comparing the skeletonized image data magnitudes to a gradient threshold and producing simplified image data representative of edges of image elements when said skeletonized image data magnitude exceeds said gradient threshold, the gradient threshold being determined to eliminate data having gradient values lower than that expected from a target edge; and
a candidate target identifier identifying candidate targets by examining the number of edge directions within the data defined by the target box size surrounding each pixel of said simplified image data based on the number of directions of edge image data present in a region of said image. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33)
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34. In a computer processing environment, a computer data storing medium storing a computer program, the computer program, when controlling the computer processing environment, performing the steps of:
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receiving image data;
applying a gradient operator to determine gradient magnitude and direction of the pixels of said image data to produce gradient image data;
skeletonizing the gradient image data to remove unnecessary detail to produce skeletonized image data representing the image primarily by the edges of the objects contained therein;
applying atmospheric compensation to said gradient image data to adjust the skeletonized image data magnitudes in relationship to range;
defining at least one target size box related to the expected target size in the image data;
establishing a gradient threshold level under which the image data is determined to be unrelated to a target edge;
thresholding the skeletonized image data by comparing the skeletonized image data magnitudes to said gradient threshold and producing simplified image data representative of edges of image elements when said skeletonized image data magnitude exceeds said gradient threshold determined in said step of establishing; and
identifying candidate targets within said skeletonized image data by examining the number of different edge directions within the data defined by the target box size surrounding each pixel of each image data element of said simplified image data based on the number of directions of edge image data present in a region of said image.
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35. A method for detecting targets within an image comprising:
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receiving image data;
applying a gradient operator to determine gradient magnitude and direction of the pixels of said image data;
establishing a gradient threshold level under which the image data is determined to be unrelated to a target edge, said gradient threshold being varied based on local gradient variance within the image data of a single image view;
comparing the gradient magnitude of said image data to said gradient threshold to produce simplified image data representative of edges of image elements; and
identifying candidate targets within said image based on the number of directions of edge image data present in a region of said image. - View Dependent Claims (36, 37, 38, 39, 40, 41, 42)
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43. A system for detecting targets within an image from received image data comprising:
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a gradient processor applying a gradient operator to determine gradient magnitude and direction of the pixels of said image data to produce gradient image data;
a threshold determiner establishing a gradient threshold level under which the image data is determined to be unrelated to a target edge, said gradient threshold being varied based on local gradient variance within the image data of a single image view;
a thresholder comparing the gradient magnitude of said image data to said gradient threshold produced by said threshold determiner to produce simplified image data representative of edges of image elements; and
a candidate target identifier identifying candidate targets by examining the number of edge directions within the data present in a region of said image. - View Dependent Claims (44, 45, 46, 47, 48, 49)
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50. In a computer processing environment, a computer data storing medium storing a computer program, the computer program, when controlling the computer processing environment, performing the steps of:
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receiving image data;
applying a gradient operator to determine gradient magnitude and direction of the pixels of said image data;
establishing a gradient threshold level under which the image data is determined to be unrelated to a target edge, said gradient threshold being varied based on local gradient variance within the image data of a single image view;
comparing the gradient magnitude of said image data to said gradient threshold to produce simplified image data representative of edges of image elements; and
identifying candidate targets within said image based on the number of directions of edge image data present in a region of said image.
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51. A method for detecting targets within an image comprising:
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receiving image data;
simplifying the image data to remove unnecessary detail to produce simplified image data representing the image primarily by the edges of the objects contained therein;
applying atmospheric compensation to said simplified image data to adjust the simplified image data magnitudes in an amount related to range, and examining the simplified image data to investigate the presence of candidate targets therein. - View Dependent Claims (52, 53, 54, 58)
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55. A system for detecting targets within an image from received image data comprising:
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a simplifier simplifying the image data by removing unnecessary detail to produce simplified image data representing the image primarily by the edges of the objects contained therein;
an atmospheric compensator applying atmospheric compensation to said simplified image data to adjust the simplified image data magnitudes in an amount related to range, and a candidate target identifier examining the simplified image data to investigate the presence of candidate targets therein. - View Dependent Claims (56)
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57. The system of claim 57 further comprising a gradient processor applying a gradient operator to determine gradient magnitude and direction of the pixels of said image data to produce gradient image data.
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59. A method for detecting targets within an image comprising:
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receiving image data;
producing a target box sized in relation to the expected target size within the image data;
examining the image data defined by the target box surrounding a pixel of said image data to investigate the presence of a target within the target box surrounding that pixel by processing the image data within said target box to determine the presence of a candidate target; and
repeating the step of examining for pixels within the image view. - View Dependent Claims (60, 61, 62, 63, 64, 65)
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66. A system for detecting targets within an image from image data thereof comprising:
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a target box generator producing a target box sized in relation to the expected target size within the image data;
a candidate target detector examining the image data defined by the target box surrounding a pixel of said image data to investigate the presence of a target within the target box surrounding that pixel by processing the image data within said target box to determine the presence of a candidate target, the examination of the image data being performed for each pixel of the data. - View Dependent Claims (67, 68, 69, 70, 71, 72)
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73. In a computer processing environment, a computer data storing medium storing a computer program, the computer program, when controlling the computer processing environment, performing the steps of:
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receiving image data;
receiving image data;
producing a target box sized in relation to the expected target size within the image data;
examining the image data defined by the target box surrounding a pixel of said image data to investigate the presence of a target within the target box surrounding that pixel by processing the image data within said target box to determine the presence of a candidate target; and
repeating the step of examining for pixels within the image view.
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74. A method for detecting targets within an image comprising:
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receiving image data;
simplifying the image data to remove unnecessary detail to produce simplified image data representing the image primarily by the edges of the objects contained therein;
attenuating horizontally oriented edges in said simplified image data to attenuate any undue masking effect they may have on adjacent non-horizontal pixels; and
examining the simplified image data to investigate the presence of candidate targets therein. - View Dependent Claims (75, 76, 77)
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78. A system for detecting targets within an image from image data thereof comprising:
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a simplifier simplifying the image data to remove unnecessary detail to produce simplified image data representing the image primarily by the edges of the objects contained therein;
a horizontal edge attenuator attenuating horizontally oriented edges in said simplified image data to attenuate any undue masking effect they may have on adjacent non-horizontal pixels; and
a candidate target examiner examining the simplified image data to investigate the presence of candidate targets therein. - View Dependent Claims (79, 80, 81)
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82. In a computer processing environment, a computer data storing medium storing a computer program, the computer program, when controlling the computer processing environment, performing the steps of:
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receiving image data;
simplifying the image data to remove unnecessary detail to produce simplified image data representing the image primarily by the edges of the objects contained therein;
attenuating horizontally oriented edges in said simplified image data to attenuate any undue masking effect they may have on adjacent non-horizontal pixels; and
examining the simplified image data to investigate the presence of candidate targets therein.
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Specification