Experiments using Liquid Crystal Televisions (LCTVs) as spatial light modulators for optical correlators, and optical input devices, have been reported upon widely. Moreover, applications of these devices for target recognition and automatic inspection systems are well documented. These systems often require the implementation of computer pre- and post- processing for image filtering and target recognition which handicaps real-time optical processing applications. It is possible to construct custom reference gratings that form a desired moire pattern when mixed with images of structurally illuminated targets. The moire patterns can be in any form, from equal depth contours, to error maps, to any arbitrary pattern desired. We have demonstrated video methods to generate such error maps in real-time. Furthermore, we have removed restrictions on the shape of the output moire contours, thus, developing a real-time automated inspection system based on the optical processing of arbitrary moire contours. We chose the moire pattern to be in the form of a Fresnel zone plate which is sent to an LCTV. Illumination of this zone plate with parallel coherent light results in a diffracted beam which produces a focused line on a detector. The result is a mixed video- optical processing system that could be used for real-time quality level sorting or other automated inspection requirements.
We have developed a system which confirms the identity of an object based on its three-dimensional surface shape. The system's two key elements are a computer routine which manipulates a desired two-dimensional output pattern and a light projector which illuminates test objects with this pattern. The operation of the system is based on prior knowledge of the surface shape for the object of interest, as determined by a previously developed machine vision system. A projection pattern is chosen to be the identifying cue to the observer for that object. For example, a set of parallel lines, a circle, or the word "pass" could all be used to signify that a particular object is being examined. This pattern is then distorted by the computer in a way which is determined by the surface shape data and projection and viewing angles for the system. This new pattern is, in a sense, an encrypted form of the original pattern. Only the original object holds the key to "undistorting" this projection pattern so that it may take on its original form. Any other object placed into the system to be examined only further distorts the pattern. Thus, by examining the projected patterns on objects being inspected, an object of interest can be distinguished from others. The simplicity of this system gives it potential for inspection and security applications in which the key issue may not be the actual surface shape, but rather a quick verification of an object's or person's identity.
A common problem in fabrication and welding of complex structures is that there is no simple way to determine where to cut one part so that it will fit another part unless both parts designed and built on a CAD/CAM system. Particularly in prototype or retrofit work, cutting and fitting parts for welding is more of an art than a science. We have developed a unique video moire system that generates the intersection contour in near real time with the contour superimposed on a video image of the part, allowing the cut line to be marked while following the contour on the video monitor.
A novel automated inspection technique to recognize, locate, and quantify damage is developed. This technique is based on two already existing technologies: video moire metrology and artificial neural networks. Contour maps generated by video moire techniques provide an accurate description of surface structure that can then be automated by means of neutral networks. Artificial neural networks offer an attractive solution to the automated interpretation problem because they can generalize from the learned samples and provide an intelligent response for similar patterns having missing or noisy data. Two dimensional video moire images of pipes with dents of different depths, at several rotations, were used to train a multilayer feedforward neural network by the backpropagation algorithm. The backpropagation network is trained to recognize and classify the video moire images according to the dent's depth. Once trained, the network outputs give an indication of the probability that a dent has been found, a depth estimate, and the axial location of the center of the dent. This inspection technique has been demonstrated to be a powerful tool for the automatic location and quantification of structural damage, as illustrated using dented pipes.
Moire techniques can be a powerful tool to determine deviation of a manufactured shape from a desired shape. In a traditional moire system, distorted gratings on an object are viewed through an undistorted grating. The moire contours that result represent equal depth contours over the entire viewed surface. By generating the moire patterns in video, it is possible to view the distorted gratings on a test object through a set of gratings that has been distorted by a similar but perfect object. The output is then a set of moire contours that corresponds to the differences between the two surfaces. This difference or error map eliminates much of the unnecessary information generated in traditional moire inspection and thus becomes a valuable tool for comparisons between an imperfect test object and a manufacturing standard. We have developed a variable resolution video system for creating this error map using a Michelson interferometer to generate the gratings. We have successfully applied this system to damage detection on a long, continuous lengths of pipe by having two side-by-side cameras looking at different sections of pipe and also by having one camera's view filtered with a video-taped recording of an undamaged section of the pipe.
Several methods for generation of three dimensional surface shapes from variable resolution video moire contours are described. In a classical moire system, a physical grating is projected on a target and also used to view the target. The moire contours are generated in the plane of the viewing grating. An unambiguous surface shape can then be computed by processing a set of moire images where the grating, target, or both are moved. By using an interferometer to generate and project variable pitch gratings and video technology to generate the moire contours, a 3-D surface can be scanned at different resolutions and used on a wide range of object sizes. The elimination of the physical grating also leads to surface generation techniques that do not use moving parts, increasing reliability. From these video moire contours, it is possible to uniquely reconstruct the 3-D surface, making the distinction between concave and convex surfaces. In one technique, a computer is used to mix digitized images of distorted gratings projected on the object with computer generated gratings, creating the moire patterns. By shifting one grating, it is possible to reconstruct the surface without having to move the object being scanned.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.