Abstract: The present disclosure provides an information processing device including an acquisition unit, a processing unit and an output unit.

Abstract: An imaging condition setting system sufficiently reduces the effects of ambient light in designing optimized illumination patterns for imaging an inspection target. The system includes an imager that captures an image of a workpiece being the inspection target, an illuminator including a light source that illuminates the workpiece with light, and an imaging condition setter that sets an imaging condition to capture an image of the workpiece. The imaging condition setter sets, for the image captured with light from the illuminator to the workpiece at a luminosity greater than or equal to a threshold, an exposure time of the imager to cause a value of a pixel in a specific area of the image of the workpiece to be within a specific range.

Abstract: An information processing system includes an imaging controller that obtains N range images of a teaching object captured with the range image sensor at N imaging positions, where N>M, a data generator that generates a plurality of composite data pieces from a plurality of different combinations of the N range images, and a determiner that calculates accuracy of each of the plurality of composite data pieces indicating a degree of matching between the composite data piece and the teaching object and determines M imaging positions from the N imaging positions based on the accuracy of each of the plurality of composite data pieces.

Abstract: This inspection device comprises: image-capturing unit obtaining an evaluation workpiece image that is captured with a plurality of predetermined illumination light emission patterns; image area setting unit setting a plurality of image areas associated with a plurality of different labels; optimization calculation unit generating a first index of which the output value increases as a difference between an image area associated with a non-defective label and a defective label increases, and a second index of which the output value increases as a difference or contrast between the image areas associated with the non-defective label increases, and calculates an illumination light emission pattern for inspection such that the first index becomes larger and the second index becomes smaller; and determination unit performing image processing on an inspection workpiece image captured with the illumination light emission pattern for inspection, and determines a pass/fail label of a workpiece to be inspected.

Abstract: Provided is an image capture method including: illuminating an object having known label data, capturing images of the object using illumination parameters, and acquiring captured images; generating an estimated image of the object at the time of illumination based on the illumination parameter on the basis of an image data set obtained by associating a captured image with an illumination parameter; setting a maximum number of captured images permitted for the object; and performing learning with a machine learning model for each number of images equal to or smaller than the maximum number of captured images, optimizing illumination parameters and inspection algorithm parameters on the basis of a result of comparison between a result of estimation of the machine learning model and the label data of the object, calculating an index representing inspection performance expected when the each number of images is captured, and presenting the index to a user.

Abstract: Provided an imaging system, an imaging apparatus and an image processing apparatus constituting the imaging system, an image processing method used in the image processing apparatus, and a non-transitory recording medium for causing a computer to implement the image processing method. According to the imaging apparatus according to one aspect of the present invention, an image of high image quality can be acquired (reconstructed) in the imaging system configured to include the imaging apparatus by acquiring first and second projected images using Fresnel zone plates having different phases of local spatial frequencies. In addition, the design parameters (pitches and the areas of the Fresnel zone plates, the number of pixels of image sensors, a distance between the Fresnel zone plates and the image sensors, and the like) can be selected without considering an effect of a noise component, and the number of restrictions on the design parameters is small.

Abstract: The present disclosure relates to a method, device, system and computer-program product for setting a lighting condition when an object is checked and a storage medium. The method includes that: the object is lighted by light sources capable of changing lighting parameters, and the object is captured by an image sensor in such lighting parameters to obtain captured images, wherein the object has known label data; and a part of or all of the captured images and the corresponding label data of the object are applied to learning of a machine learning model, and the lighting condition and the check algorithm parameters of the machine learning model is set simultaneously by optimizing both the lighting parameters and the check algorithm parameters, on the basis of a comparison result between an estimation result of the machine learning model and the label data. Therefore, operations are simplified.

Abstract: The present disclosure relates to a method, device, system and computer-program product for setting a lighting condition when an object is checked and a storage medium. The method includes that: the object is lighted by light sources capable of changing lighting parameters specifying the lighting condition when the object is captured, and the object with corresponding label data is captured by an image sensor under multiple such lighting parameters to obtain multiple captured images; estimation images of the object are generated on the basis of image data sets obtained by associating the captured images and the corresponding lighting parameters; and the estimation images and the corresponding label data are applied to learning of the machine learning model, and the lighting condition is set on the basis of a comparison result between an estimation result of a machine learning model and the label data. Therefore, operations are simplified.

Abstract: Provided an imaging system, an imaging apparatus and an image processing apparatus constituting the imaging system, an image processing method used in the image processing apparatus, and a non-transitory recording medium for causing a computer to implement the image processing method. According to the imaging apparatus according to one aspect of the present invention, an image of high image quality can be acquired (reconstructed) in the imaging system configured to include the imaging apparatus by acquiring first and second projected images using Fresnel zone plates having different phases of local spatial frequencies. In addition, the design parameters (pitches and the areas of the Fresnel zone plates, the number of pixels of image sensors, a distance between the Fresnel zone plates and the image sensors, and the like) can be selected without considering an effect of a noise component, and the number of restrictions on the design parameters is small.

Abstract: An image processing apparatus according to one aspect of the present invention includes a projected image input unit that inputs a projected image formed by light incident on a Fresnel zone plate from a subject, a complex image generation unit that generates a complex image including an image of a real part and an image of an imaginary part by multiplying the projected image with each of a first Fresnel zone pattern and a second Fresnel zone pattern having the same local spatial frequency in each region and a different phase of the local spatial frequency with respect to the first Fresnel zone pattern, and a Fourier transformation unit that reconstructs an image of a spatial domain by performing two-dimensional complex Fourier transformation on the complex image.

Abstract: Provided are an image-processing system, an image-processing device, an image-processing method, and an image-processing program capable of appropriately inspecting, measuring, or recognizing targets by using a plurality of imaging units even in a case where there is an individual difference in performance of each imaging unit. An image correction-processing unit that individually acquires pieces of image data from a first camera and a second camera to individually correct image deterioration caused by each of the cameras by pieces of image-processing and an inspection processing unit that individually acquires the pieces of image data after the correction from the image correction-processing unit to individually inspect imaged targets by pieces of image-processing are provided.

Abstract: Provided are an imaging apparatus, a signal processing method for an imaging apparatus, and a non-transitory computer readable recording medium storing a signal processing program for an imaging apparatus capable of capturing a high quality image with a compact configuration. An imaging lens 10A is composed of, in order from an object side, a first lens group G1 that is fixed during variable magnification, a second lens group G2 and a third lens group G3 that move during variable magnification, and a fourth lens group G4 that is fixed during variable magnification. The first lens group G1 is composed, in order from the object side, a first-a lens group G1a that is fixed during focusing, a first-b lens group G1b that moves during focusing, and a first lens group rear group G1c that is fixed during focusing. Fluctuation of an angle of view with focusing is corrected through image processing.

Abstract: An image processing device includes a transfer function input unit to which each of transfer functions of a plurality of imaging systems is input, a calculation unit that calculates a target resolution value which is a target value of recovery processing that recovers a plurality of captured images to be output from each of the plurality of the imaging systems based on the input transfer functions and a predetermined criterion, a recovery-filter generation unit that generates a recovery-filter used for the recovery processing with respect to each of the plurality of imaging systems based on the transfer functions of the plurality of imaging systems and a target resolution value, and a recovered image generation unit that performs the recovery processing with respect to the captured images acquired from the plurality of imaging systems by using the recovery-filter generated for each of the plurality of imaging systems to generate recovered images.

Abstract: An image processing device includes a transfer function input unit to which each of transfer functions of a plurality of imaging-systems is input, a calculation unit that calculates a target resolution value which is a target value of recovery processing that recovers a plurality of captured images to be output from each of the plurality of the imaging-systems based on each of the input transfer functions and a predetermined criterion, a recovery filter generation unit that generates a recovery filter used for the recovery processing with respect to each of the plurality of imaging-systems based on each of the transfer functions of the plurality of imaging-systems and a target resolution value, and a recovered image generation unit that performs the recovery processing with respect to the captured images acquired from the plurality of imaging-systems by using the recovery filter generated for each of the plurality of imaging-systems to generate recovered images.

Abstract: Provided are an image processing device, an image processing method, and a non-transitory computer readable recording medium storing a program which generate a favorable-quality combination image of which distortion is partially corrected with no calculation cost. A plurality of images captured by a plurality of cameras is input, and scaling processing is performed on at least one image of two images to be combined with each other among the plurality of images in a direction perpendicular to a direction in which the two images are combined. A continuous combination image is generated by combining the plurality of images after the scaling processing. The scaling processing is performed on at least the one image of the two images according to a predetermined scaling ratio, and a misalignment on an image of a combined portion of the two images to be combined with each other in the perpendicular direction is suppressed.