Image processing device, program, image processing method, computer-readable medium, and image processing system
First Claim
Patent Images
1. An image processing apparatus comprising:
- at least one hardware processor configured to implement;
a setting unit configured to set an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances;
a calculation unit configured to calculate a Histograms of Oriented Gradients (HOG) feature quantity in each of the plurality of captured images based on a luminance gradient direction and intensity in the object region and to calculate a vector obtained by combining the calculated HOG feature quantities as an image feature quantity; and
a determination unit configured to determine whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell.
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Abstract
An image processing device 20 acquires a plurality of captured images obtained by imaging a sample including a target cell at a plurality of different focal distances, sets an object region for detecting the target cell in at least two of the plurality of captured images, and performs determination about whether or not the target cell is included in the object region based on whether or not an image feature quantity based on change in image information in an image in-plane direction and a focal distance direction of an image in the object region in the plurality of captured images satisfies conditions defined for the target cell.
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Citations
17 Claims
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1. An image processing apparatus comprising:
at least one hardware processor configured to implement; a setting unit configured to set an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; a calculation unit configured to calculate a Histograms of Oriented Gradients (HOG) feature quantity in each of the plurality of captured images based on a luminance gradient direction and intensity in the object region and to calculate a vector obtained by combining the calculated HOG feature quantities as an image feature quantity; and a determination unit configured to determine whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell. - View Dependent Claims (4, 5, 6, 10, 11)
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2. An image processing apparatus comprising:
at least one hardware processor configured to implement; a setting unit configured to set an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; a calculation unit configured to calculate a Histograms of Oriented Gradients (HOG) feature quantity in each difference image between two captured images adjacent in focal distance among the plurality of captured images based on a luminance gradient direction and intensity in the object region and to calculate a vector obtained by combining the calculated HOG feature quantities as an image feature quantity; and a determination unit configured to determine whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell. - View Dependent Claims (7, 8, 9)
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3. An image processing apparatus comprising:
at least one hardware processor configured to implement; a setting unit configured to set an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; a calculation unit configured to calculate a three-dimensional Histograms of Oriented Gradients (HOG) feature quantity as an image feature quantity based on a three-dimensional luminance gradient direction having an in-plane direction and a focal distance direction of the plurality of captured images in the object region and intensity; and a determination unit configured to determine whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell.
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12. An image processing method that causes a computer to execute a process comprising:
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setting an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; calculating a Histograms of Oriented Gradients (HOG) feature quantity in each of the plurality of captured images based on a luminance gradient direction and intensity in the object region and calculating a vector obtained by combining the calculated HOG feature quantities as an image feature quantity; and determining whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell.
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13. An image processing method that causes a computer to execute a process comprising:
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setting an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; calculating a Histograms of Oriented Gradients (HOG) feature quantity in each difference image between two captured images adjacent in focal distance among the plurality of captured images based on a luminance gradient direction and intensity in the object region and calculating a vector obtained by combining the calculated HOG feature quantities as an image feature quantity; and determining whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell.
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14. An image processing method that causes a computer to execute a process comprising:
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setting an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; calculating a three-dimensional Histograms of Oriented Gradients (HOG) feature quantity as an image feature quantity based on a three-dimensional luminance gradient direction having an in-plane direction and a focal distance direction of the plurality of captured images in the object region and intensity; and determining whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell.
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15. A non-transitory computer readable medium storing a program causing a computer to execute a process for image processing, the process comprising:
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setting an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; calculating a Histograms of Oriented Gradients (HOG) feature quantity in each of the plurality of captured images based on a luminance gradient direction and intensity in the object region and calculating a vector obtained by combining the calculated HOG feature quantities as an image feature quantity; and determining whether the target cell is included in the object region based on whether or not the image feature quantity satisfies conditions defined for the target cell.
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16. A non-transitory computer readable medium storing a program causing a computer to execute a process for image processing, the process comprising:
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setting an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; calculating a Histograms of Oriented Gradients (HOG) feature quantity in each difference image between two captured images adjacent in focal distance among the plurality of captured images based on a luminance gradient direction and intensity in the object region and calculating a vector obtained by combining the calculated HOG feature quantities as an image feature quantity; and determining whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell.
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17. A non-transitory computer readable medium storing a program causing a computer to execute a process for image processing, the process comprising:
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setting an object region for detecting a target cell in each of a plurality of captured images obtained by imaging a sample including the target cell at a plurality of different focal distances; calculating a three-dimensional Histograms of Oriented Gradients (HOG) feature quantity as an image feature quantity based on a three-dimensional luminance gradient direction having an in-plane direction and a focal distance direction of the plurality of captured images in the object region and intensity; and determining whether the target cell is included in the object region based on whether the image feature quantity satisfies conditions defined for the target cell.
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Specification