Abstract: A line segment detection method includes acquiring an image, extracting from the image a straight line that includes a line segment, acquiring a luminance distribution of the straight line, generating a virtual function model that contains a distribution of a foreground and a background of the image by using the luminance distribution, and determining whether luminance values near end points (start point and end point) of the line segment contained in the virtual function model probabilistically belong to the foreground or the background, and estimating end points (start point and end point) in the virtual function model.

Abstract: A moving body observation method includes acquiring time-series images taken at a predetermined time interval, obtaining an estimated position of a moving body in the time-series image based on an estimated motion of the moving body, extracting an image including the estimated position of the moving body from images of the time-series images, as an extracted image, generating a template image by stacking the extracted images in such a manner that reference points of the moving body in the extracted images coincide with each other, and identifying a position of the moving body in each of the time-series images by performing template matching using the template image for at least one of the time-series images.

Abstract: A line segment detection method includes acquiring an image, extracting from the image a straight line that includes a line segment, acquiring a luminance distribution of the straight line, generating a virtual function model that contains a distribution of a foreground and a background of the image by using the luminance distribution, and determining whether luminance values near end points (start point and end point) of the line segment contained in the virtual function model probabilistically belong to the foreground or the background, and estimating end points (start point and end point) in the virtual function model.