Abstract: A non-transitory computer-readable recording medium having stored an image processing program that causes a computer to execute a process, the process includes extracting a plurality of consecutive pixels corresponding to a first part or a second part of a body, from a pixel column in a predetermined direction of an image of the body, obtaining a statistical value of pixel values of the plurality of consecutive pixels, and identifying a part corresponding to the plurality of consecutive pixels, among the first part or the second part, based on the statistical value.

Abstract: A lesion detection method for a computer to execute a process includes detecting a first lesion region that indicates a certain lesion from each of a plurality of tomographic images obtained by imaging an inside of a human body, by using a first machine learning model that detects a lesion region from an input image that has image data of a two-dimensional space; detecting a second lesion region that indicates the certain lesion from three-dimensional volume data generated based on the plurality of tomographic images, by using a second machine learning model that detects a lesion region from input volume data that has image data of a three-dimensional space; and detecting a third lesion region that indicates the certain lesion from each of the plurality of tomographic images, based on an overlapping state between the first lesion region and the second lesion region.

Abstract: A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process includes identifying first filter processing applied to a first image that is training data used for machine learning; generating the first image from which characteristics of the identified first filter processing are removed; and generating, by applying second filter processing to the first image from which the characteristics are removed, a second image to be assigned a label identical to a label of the first image, the second image being used in the machine learning as the training data.

Abstract: A non-transitory computer-readable recording medium having stored an image processing program that causes a computer to execute a process, the process includes extracting a plurality of consecutive pixels corresponding to a first part or a second part of a body, from a pixel column in a predetermined direction of an image of the body, obtaining a statistical value of pixel values of the plurality of consecutive pixels, and identifying a part corresponding to the plurality of consecutive pixels, among the first part or the second part, based on the statistical value.

Abstract: A device that determines whether a first person extracted from a first image is identified with a second person extracted from a second image, includes a processor configured to extract a first feature value of a contour portion of the first person, from the first image, extract a second feature value of a contour portion of the second person, from the second image, and determine whether the first person is identified with the second person, based on comparison processing in which a first effect on a first comparison result of the first feature value and the second feature value becomes greater than a second effect on a second comparison result of a third feature value of a portion further from a contour than the contour portion of the first person and a fourth feature value of a portion further from the contour than the contour portion of the second person.

Abstract: An apparatus for identifying a candidate area in a first image corresponding to an object in a second image, includes a memory and a processor to divide the plurality of candidate areas into a plurality of small candidate areas, divide an image area of the object into a plurality of small areas, perform first comparison processing for a first part, when there is a first candidate area lacking image information of the small candidate area corresponding to the first part, perform second comparison processing for a second part, predict missing result on the small candidate area corresponding to the first part in the first candidate area based on a result of the first comparison processing on a candidate area other than the first candidate area, and a result of the second comparison processing on the plurality of candidate areas, and identify the candidate area based on a prediction.

Abstract: An image processing method for tracking an object, the method includes: specifying a first range in which a first target is searched for and a second range in which a second target is searched for in a next frame by referring to a storage device that stores past frames captured by a capturing device; changing the first range and/or the second range in the next frame such that an area in which the first range and the second range specified in the next frame overlap each other is less than a predetermined value in a case where the overlapping area is equal to or greater than the predetermined value; and searching for, in the changed first range and the changed second range, and specifying a region corresponding to the first target and a region corresponding to the second target in the next frame.

Abstract: A search system includes circuitry configured to detect an first object to be a search target, from information of an image that is captured by an imaging device, determine a parameter in consideration of how the first object is viewed in the image, in accordance with a height at which the imaging device is installed, a depression angle of the imaging device, and a distance from the imaging device to the first object, divide an image region corresponding to the first object into at least two image regions based on a dividing ratio that is obtained by correcting a predetermined ratio in accordance with the parameter, and specify a second object in another image based on feature information of each of the at least two image regions, the second object corresponding to the first object in the image.

Abstract: An apparatus for identifying a candidate area in a first image corresponding to an object in a second image, includes a memory and a processor to divide the plurality of candidate areas into a plurality of small candidate areas, divide an image area of the object into a plurality of small areas, perform first comparison processing for a first part, when there is a first candidate area lacking image information of the small candidate area corresponding to the first part, perform second comparison processing for a second part, predict missing result on the small candidate area corresponding to the first part in the first candidate area based on a result of the first comparison processing on a candidate area other than the first candidate area, and a result of the second comparison processing on the plurality of candidate areas, and identify the candidate area based on a prediction.

Abstract: A non-transitory computer-readable storage medium storing an event detection program that causes a computer to perform a process, the process including acquiring a first captured image captured at a first timing by a first camera device, acquiring a second captured image captured at a second timing after the first timing by a second camera device, detecting an event in accordance with a first image feature extracted from the first captured image, a second image feature extracted from the second captured image and an event detection criteria, the event detection criteria making the event less detectable as a variance of the first image feature or a variance of the second image feature is smaller, both the first image feature and the second image feature corresponding to one or more target objects, and outputting a result of the detecting of the event.

Abstract: A moving object group detection method includes: respectively analyzing a first captured image captured by a first image capture device and a second captured image captured by a second image capture device, and respectively extracting a first image region and a second image region from the first captured image and the second captured image, the first image region and the second image region being regions in which coloring patterns satisfy a predetermined similarity range and moving in corresponding directions over plural frames; and detecting that a common moving object group is included in the first image region and the second image region on the basis of an evaluation of similarity between an image within the first image region and an image within the second image region.

Abstract: An image processing method for tracking an object, the method includes: specifying a first range in which a first target is searched for and a second range in which a second target is searched for in a next frame by referring to a storage device that stores past frames captured by a capturing device; changing the first range and/or the second range in the next frame such that an area in which the first range and the second range specified in the next frame overlap each other is less than a predetermined value in a case where the overlapping area is equal to or greater than the predetermined value; and searching for, in the changed first range and the changed second range, and specifying a region corresponding to the first target and a region corresponding to the second target in the next frame.

Abstract: An apparatus for identifying a candidate area in a first image corresponding to an object in a second image, includes a memory and a processor to divide the plurality of candidate areas into a plurality of small candidate areas, divide an image area of the object into a plurality of small areas, perform first comparison processing for a first part, when there is a first candidate area lacking image information of the small candidate area corresponding to the first part, perform second comparison processing for a second part, predict missing result on the small candidate area corresponding to the first part in the first candidate area based on a result of the first comparison processing on a candidate area other than the first candidate area, and a result of the second comparison processing on the plurality of candidate areas, and identify the candidate area based on a prediction.

Abstract: A non-transitory computer-readable storage medium storing an image processing device that causes a computer to execute a process includes: individually detecting, as a detection target candidate, a first portion of each of detection targets that appear in an image imaged by an imaging device, by using a first detection area corresponding to the first portion; detecting a detection target for a detection target candidate corresponding to a detection target that is not covered by another detection target and that is included in the detected detection target candidates, by using a second detection area corresponding to a second portion including the first portion; and detecting a detection target for a detection target candidate corresponding to a detection target, covered by another detection target and included in the detected detection target candidates, by using a third detection area that corresponds to a third portion including the first portion.

Abstract: A search system includes circuitry configured to detect an first object to be a search target, from information of an image that is captured by an imaging device, determine a parameter in consideration of how the first object is viewed in the image, in accordance with a height at which the imaging device is installed, a depression angle of the imaging device, and a distance from the imaging device to the first object, divide an image region corresponding to the first object into at least two image regions based on a dividing ratio that is obtained by correcting a predetermined ratio in accordance with the parameter, and specify a second object in another image based on feature information of each of the at least two image regions, the second object corresponding to the first object in the image.

Abstract: A non-transitory computer-readable storage medium storing an image processing device that causes a computer to execute a process includes: individually detecting, as a detection target candidate, a first portion of each of detection targets that appear in an image imaged by an imaging device, by using a first detection area corresponding to the first portion; detecting a detection target for a detection target candidate corresponding to a detection target that is not covered by another detection target and that is included in the detected detection target candidates, by using a second detection area corresponding to a second portion including the first portion; and detecting a detection target for a detection target candidate corresponding to a detection target, covered by another detection target and included in the detected detection target candidates, by using a third detection area that corresponds to a third portion including the first portion.

Abstract: A device that determines whether a first person extracted from a first image is identified with a second person extracted from a second image, includes a processor configured to extract a first feature value of a contour portion of the first person, from the first image, extract a second feature value of a contour portion of the second person, from the second image, and determine whether the first person is identified with the second person, based on comparison processing in which a first effect on a first comparison result of the first feature value and the second feature value becomes greater than a second effect on a second comparison result of a third feature value of a portion further from a contour than the contour portion of the first person and a fourth feature value of a portion further from the contour than the contour portion of the second person.

Abstract: An apparatus for identifying a candidate area in a first image corresponding to an object in a second image, includes a memory and a processor to divide the plurality of candidate areas into a plurality of small candidate areas, divide an image area of the object into a plurality of small areas, perform first comparison processing for a first part, when there is a first candidate area lacking image information of the small candidate area corresponding to the first part, perform second comparison processing for a second part, predict missing result on the small candidate area corresponding to the first part in the first candidate area based on a result of the first comparison processing on a candidate area other than the first candidate area, and a result of the second comparison processing on the plurality of candidate areas, and identify the candidate area based on a prediction.