Abstract: A method and system are described for use at a machine vision station to correctly identify flaws within a sample image by means of flexible template image comparison where the template image and a sample image suffer from a relative geometrical distortion. The method and system use the following iterative approach: 1) generate the template image; 2) register the sample image to the template image; 3) undertake an absolute image subtraction process; 4) identify all regions of image difference; 5) create sub-images of both the template and the sample images in the region of detected error; 6) repeat the registration step 2) using the sub-images; 7) undertake the absolute subtraction process on each of the sub-images; and 8) either identify the resulting differences as flaws or go to step 5) using even smaller sub-images. The invention has particular utility in the screen printing industry as well as other industries.

Abstract: An optical method and system for measuring three-dimensional surface topography by providing high resolution contour measurements of an object using interferometric methods. The invention utilizes co-sight detector technology to provide at least three independent images of exactly the same object location, with a known fringe pattern optically introduced to each of the images. Each of the fringe patterns have a known phase difference relative to the phase appearing on each of the other images. Furthermore, the images have the same perspective relative to the object and may be collected simultaneously. This simultaneous collection of multiple phase images allows very high speed 3D data generation. Previous limitations of phase shift technology such as sample motion and vibration can be eliminated. The method may use continuous or strobed illumination.

Abstract: A method and system are provided for identifying an image feature of an object. The system preferably includes a machine vision system for capturing an original color image of the object in a first color space defined by a first set of color axes to obtain a first set of image data. The first set of image data is transformed within the machine vision system to a second set of image data in an optimal color space having an optimal set of color axes which define an optimal direction wherein the amount of inter axis correlation of the second set of image data is minimized. The machine vision system then manipulates the second set of image data to identify the image feature. Color differences existing in the original color image are amplified and separation between chromatically different regions of the original color image are maximized in the optimal color space. Preferably, the optimal set of color axes are three orthogonal axes. The first set of image data is rotated to match the optimal direction.