Abstract: An image processing apparatus includes: a gradient information calculating unit that calculates gradient information of each of pixels, based on pixel values of an intraluminal image; a closed region creating unit that, based on the gradient information, creates a closed region satisfying a condition where the closed region does not include, on the inside thereof, any pixel of which the gradient strength is equal to or higher than a predetermined value, and also, the boundary of the closed region does not curve toward the interior of the closed region, with a curvature equal to or larger than a predetermined value; and an abnormal part detecting unit that detects an abnormal part from the inside of the closed region.

Abstract: An image processing apparatus includes a feature-quantity calculating unit that calculates feature quantities of target regions each indicating a tracking object in respective target images, the target images being obtained by capturing the tracking object at a plurality of time points; a provisional-tracking processing unit that performs provisional tracking of the target region by associating the target regions of the target images with each other using the calculated feature quantities; and a final-tracking processing unit that acquires a final tracking result of the target region based on a result of the provisional tracking.

Abstract: An image processing apparatus includes: a category area dividing unit that divides each image constituting the time-series images of an object to be examined, which are captured in time series, into category areas including an examined area and an abnormal candidate area, the examined area showing the object to be examined, the abnormal candidate area being possibly an abnormal area showing an abnormal site of the object to be examined; an optical flow calculator that calculates optical flows of the examined area and the abnormal candidate area from images constituting the time-series images; and an abnormal area detector that compares the optical flow of the examined area and the optical flow of the abnormal candidate area, and detects the abnormal candidate area as the abnormal area according to the result of the comparison.

Abstract: An image processing apparatus according to an embodiment that processes time-series images that include a plurality of images captured in time series includes an interval setting unit that sets a time-series interval on the basis of a variation between images of the time-series images; and an area classifying unit that performs, in an image included in the time-series interval, classification into a plurality of category areas using a classification reference for each time-series interval set by the interval setting unit.

Abstract: A learning-type classifying apparatus comprises defective region extracting unit for extracting defective regions of classification targets from an image in which the plurality of regions of the classification targets are present, characteristic value calculating unit for calculating characteristic values for the extracted regions of the classification targets, classifying unit for classifying the extracted regions of the classification targets into predetermined classes on the basis of the calculated characteristic values, region integrating unit for integrating the regions which belong to the same class as a result of the classification, display unit for displaying images of the integrated regions and the classification results, input unit for correcting errors in the classification results, and teacher data creating unit for creating teacher data for each of the regions so that the classification results of the integrated regions are reflected in each region included in the integrated regions.

Abstract: An image processing device includes a region-of-interest detecting unit that detects a region of interest from each of sequence images acquired in chronological order; a region dividing unit that divides a plurality of images temporally neighboring to each other into regions based on region-of-interest detection results obtained from the plurality of images; an inter-image variation calculating unit that calculates an inter-image variation between the plurality of images based on a variation in each region obtained by the division by the region dividing unit; and a display-condition setting unit that sets a display condition for each image based on the inter-image variation.

Abstract: A determination device includes a region information recording unit that records therein region information regarding a closed region corresponding to a data distribution shape of a same category within a feature space, the closed region being formed by a plurality of nodes and line segments connecting the plurality of nodes. The determination device also includes a category deciding unit that decides a category of a determination target based on the region information and a position of the determination target within the feature space.

Abstract: An image processing device includes a feature value calculating unit that calculates a color feature value of each pixel or each segment inside at least one of a series of images captured by an image pickup device while moving inside a gastrointestinal tract; a color feature value estimating unit that, based on data distribution of the color feature value of each pixel or each segment, estimates color feature value data representing mucous membrane and color feature value data representing gastrointestinal contents; and a discrimination boundary setting unit that, based on the estimated color feature value data, sets a color feature value discrimination boundary between mucous membrane and gastrointestinal contents.

Abstract: An image processing apparatus includes an area dividing unit that divides an image obtained by capturing inside of a body lumen into one or more areas by using a value of a specific wavelength component that is specified in accordance with a degree of absorption or scattering in vivo from a plurality of wavelength components included in the image or wavelength components obtained by conversion of the plurality of wavelength components; and a target-of-interest site specifying unit that specifies a target-of-interest site in the area by using a discriminant criterion in accordance with an area obtained by the division.

Abstract: An image display apparatus displays time-series images, and includes a display-condition receiving unit that receives at least an input that specifies a minimum display rate as a display condition for displaying each image that makes up time-series images; an importance calculating unit that calculates an importance coefficient that represents the degree of importance of each of the images; a display-time calculating unit that calculates a display time for each of the images using the display condition that is received by the display-condition receiving unit and the importance coefficient that is calculated by the importance calculating unit; and a display control unit that performs control so that the images are displayed on a display unit sequentially in a temporal order for the respective display times that are calculated by the display-time calculating unit.

Abstract: An image processing device for processing time-series intraluminal images captured by an imaging device moving in an in-vivo lumen. The image processing device includes a structural area extracting unit that extracts a structural area from the intraluminal image; a corresponding area extracting unit that extracts a corresponding area corresponding to the structural area from the intraluminal image at a second time point different from a first time point at which the structural area is extracted; a lumen deep portion extracting unit that extracts a lumen deep portion, on which a deep portion in the lumen is captured, from the intraluminal image; and a movement amount estimating unit that estimates a movement amount of the imaging device based on positions of the structural area, the corresponding area and the lumen deep portion.

Abstract: An image processing apparatus for extracting images from a continuous image sequence includes a storage unit that stores image information about images constituting the image sequence; an image reading unit that reads the image information from the storage unit; and an image change amount calculating unit that calculates a predetermined image change amount between at least two images using the image information read by the image reading unit. The apparatus also includes an image change amount information adding unit that adds information about the image change amount calculated by the image change amount calculating unit to a corresponding image; and an image extracting unit that extracts a preset number of images from the image sequence based on the information added to each image by the image change amount information adding unit.

Abstract: An image processing apparatus for performing an image processing on a body cavity image captured in a living body includes: a storage unit which stores information including image information of the body cavity image; a change amount calculator which reads out the image information of the body cavity image from the storage unit and calculates, in the read body cavity image, a pixel value change amount of a pixel of interest with a plurality of surrounding pixels located around the pixel of interest; and a candidate lesion region detector which detects a candidate lesion region in the body cavity image based on calculation result of the change amount calculator.

Abstract: An image processing apparatus includes an edge intensity calculator which calculates an edge intensity of a pixel in an image; and a correlation value calculator which calculates a correlation value between the calculated edge intensity and a bubble model set in advance based on characteristics of a bubble image. The apparatus also includes a bubble area detector which detects a bubble area based on the calculated correlation value.

Abstract: A noise reduction apparatus is disclosed. A noise amount estimating unit estimates a noise amount in a focused pixel. A smoothing unit smoothes the focused pixel. A control unit controls the smoothing unit on the basis of the noise amount and information on the focused pixel and neighboring pixels thereof.

Abstract: An image processing apparatus includes a feature-quantity calculating unit that calculates feature quantities of target regions each indicating a tracking object in respective target images, the target images being obtained by capturing the tracking object at a plurality of time points; a provisional-tracking processing unit that performs provisional tracking of the target region by associating the target regions of the target images with each other using the calculated feature quantities; and a final-tracking processing unit that acquires a final tracking result of the target region based on a result of the provisional tracking.

Abstract: An image processor that can suitably specify a predetermined area of a grayscale image is provided. An extreme value coordinate acquiring unit performs scanning on at least one of a plurality of pixels including a target pixel from the target pixel in accordance with gradient information corresponding to a change in a pixel value, and acquires a coordinate of the scanned pixel corresponding to an extreme value of the pixel value as a coordinate of an extreme value pixel corresponding to the target pixel. An area specifying unit labels each target pixel with an area identification mark used for specifying an area to which the each pixel belongs. The area specifying unit 103 labels each of different pixels corresponding to coordinates of extreme value pixels located close to each other within a particular range with an area identification mark indicating an identity of the area to which the pixels belong.

Abstract: A classification device includes area extracting unit for extracting a plurality of areas from an image, classifying unit for classifying the extracted areas into predetermined categories, and representative category deciding unit for deciding a representative category of the entire image based on a classification result of the area in the image.

Abstract: A learning-type classifying apparatus comprises defective region extracting unit for extracting defective regions of classification targets from an image in which the plurality of regions of the classification targets are present, characteristic value calculating unit for calculating characteristic values for the extracted regions of the classification targets, classifying unit for classifying the extracted regions of the classification targets into predetermined classes on the basis of the calculated characteristic values, region integrating unit for integrating the regions which belong to the same class as a result of the classification, display unit for displaying images of the integrated regions and the classification results, input unit for correcting errors in the classification results, and teacher data creating unit for creating teacher data for each of the regions so that the classification results of the integrated regions are reflected in each region included in the integrated regions.

Abstract: A noise reduction apparatus is disclosed. A noise amount estimating unit estimates a noise amount in a focused pixel. A smoothing unit smoothes the focused pixel. A control unit controls the smoothing unit on the basis of the noise amount and information on the focused pixel and neighboring pixels thereof.