Abstract: A control processing unit simultaneously drives cameras to produce images of a measuring object, the control processing unit searches corresponding point on a comparative image produced by one of the cameras for a representative point in a reference image produced by the other camera, and the control processing unit computes a three-dimensional coordinate corresponding to a coordinate using the coordinate of each point correlated by the search. The control processing unit also obtains a shift amount at the corresponding point specified by the search to an epipolar line specified based on a coordinate of a representative point on the reference image side or a parameter indicating a relationship between the cameras, and the control processing unit supplies the shift amount as an evaluation value indicating accuracy of three-dimensional measurement along with three-dimensional measurement result.

Abstract: Images of a work piece in which measurement object is restricted to a specific point or domain are taken by a camera which takes the image of the work piece from a front-view direction and a camera which takes the image from obliquely above, and a height of each measurement object region is measured. Each pixel of the front-view image used in measurement processing is virtually disposed in a three-dimensional coordinate system including x- and y-axes constituting a coordinate system of the image and a z-axis indicating the height, and a perspective transform is performed to produce a processing result image expressing measurement result. A measurement value is set as the z-coordinate at the pixel which is a height measurement object, and the z-coordinates of other pixels are set at other pixels. A mark for identifying a position and an auxiliary line indicating the height are set at measurement object points and measurement object region in the image.

Abstract: After calibration for three-dimensional measurement has been completed, specification of a range of height to be measured is accepted, and using a homography matrix corresponding to the specified range on each of the images A0 and A1 from respective cameras, a range is extracted where a point included in the viewing fields of both of the cameras appears among points in the specified height range. Further, the extracted range is color-displayed as a measurable range on each of the images A0 and A1.

Abstract: Defects in the contour of a target object is detected by obtaining an digital variable-density image of the contour and edges are extracted from the image of the contour so as to sequentially represent the contour. Their directions are measured and the direction of each edge is compared with those of other edges selected according to their distances from the edge under consideration. The differential is indicative of the presence or absence of an indentation or a protrusion in the contour, representing a defect.

Abstract: In a gray level image, the direction and the magnitude of a level gradient are found for each of pixels. With respect to the pixel having a level gradient whose magnitude exceeds a predetermined value, a line segment having a predetermined length is drawn in the direction of the level gradient from the pixel or a position spaced apart from the pixel by a predetermined distance. The luminance level of the line segment corresponds to the magnitude of the level gradient. A portion where a lot of line segments are overlapped with one another or a portion where the line segments are concentrated is detected, to recognize the center, the corners, etc. of an object appearing on the image.

Abstract: An image processing method and an image processing apparatus are disclosed, in which curved linear objects and uneven linear objects as well as rectilinear objects can be detected easily and accurately. Edge pixels P1 extracted from a gray-scale image to be processed are sequentially considered to search for an edge pixel having an opposite direction of density gradient to each of the edge pixels P1 within the range of a predetermined length W along the direction orthogonal to the edges. Once an edge pixel P2 meeting these conditions is extracted, a line segment having a length L is set extending in the direction C parallel to the edge of the edge pixels P1 from an intermediate point Q between the extracted edge pixel P2 and the edge pixel P1 under consideration.

Abstract: Plural items of two-dimensional image processing and at least one item of a three-dimensional measurement process are registered in a processing item table. The items of two-dimensional image processing include at least one item of an on-first-image position specification process of specifying a position on a physical object in a first image. A sequence building unit combines the item of the on-first-image position specification process and the item of the three-dimensional measurement process to set the sequence for three-dimensional measurement by selection of a user.

Abstract: After calibration for three-dimensional measurement has been completed, specification of a range of height to be measured is accepted, and using a homography matrix corresponding to the specified range on each of the images A0 and A1 from respective cameras, a range is extracted where a point included in the viewing fields of both of the cameras appears among points in the specified height range. Further, the extracted range is color-displayed as a measurable range on each of the images A0 and A1.

Abstract: An object of this invention is to provide an image processing method and image processing apparatus capable of extracting the position of an object in the unit of sub-pixel. An edge pixel, density gradient direction and edge position in the unit of sub-pixel are extracted from a model image obtained by photographing a high-quality model of the object and registered in a hard disk. After a processing object image is inputted, CPU obtains a position of an image region corresponding to the model image and after that, extracts an edge pixel whose edge position in the unit of sub-pixel is related to a corresponding pixel on the model image side in that image region. The edge position in the unit of sub-pixel is extracted for these edge pixels and the quantity of deviation between the extracting position and the edge position on the model image side is calculated.

Abstract: After a variable-density image of a target object is inputted and edge pixels representing the contour line of the target object are extracted from the image, the directions of these edge pixels are calculated, while straight-line portions in the contour are labeled according to their directions. Those of the edge pixels, which have the same direction as that of any of the straight-line portions, are assigned the same label. Line segments are then extracted as assemblies of those of the edge pixels which are continuous on the image and have a same assigned label. For labeling the directions of the straight-line portions, a histogram may be prepared, based on the numbers of edge pixels having different directions. Peaks are then extracted from the histogram and the labels are set to the directions corresponding to these peaks.

Abstract: An image processing method and an image processing apparatus are disclosed, in which curved linear objects and uneven linear objects as well as rectilinear objects can be detected easily and accurately. Edge pixels P1 extracted from a gray-scale image to be processed are sequentially considered to search for an edge pixel having an opposite direction of density gradient to each of the edge pixels P1 within the range of a predetermined length W along the direction orthogonal to the edges. Once an edge pixel P2 meeting these conditions is extracted, a line segment having a length L is set extending in the direction C parallel to the edge of the edge pixels P1 from an intermediate point Q between the extracted edge pixel P2 and the edge pixel P1 under consideration.

Abstract: After a variable-density image of a target object is inputted and edge pixels representing the contour line of the target object are extracted from the image, the directions of these edge pixels are calculated, while straight-line portions in the contour are labeled according to their directions. Those of the edge pixels, which have the same direction as that of any of the straight-line portions, are assigned the same label. Line segments are then extracted as assemblies of those of the edge pixels which are continuous on the image and have a same assigned label. For labeling the directions of the straight-line portions, a histogram may be prepared, based on the numbers of edge pixels having different directions. Peaks are then extracted from the histogram and the labels are set to the directions corresponding to these peaks.

Abstract: Defects in the contour of a target object is detected by obtaining an digital variable-density image of the contour and edges are extracted from the image of the contour so as to sequentially represent the contour. Their directions are measured and the direction of each edge is compared with those of other edges selected according to their distances from the edge under consideration. The differential is indicative of the presence or absence of an indentation or a protrusion in the contour, representing a defect.