A machine-vision method was used to build a three-dimensional measurement system using a measurement algorithm and a perspective transformation. The image data from a double complementary metal oxide semiconductor were transmitted to a notebook personal computer to calculate the parameters. A three-dimensional measurement system for obtaining its feature points in the world coordinate system was used to calculate the measurement data. The experimental results were verified with a more precise measurement equipment, automatic transformer observation system. The three-dimensional measurement system introduced here was applied to two case studies. The first case considered the measurement of hole diameters, such as those found in the cylinder head of an internal combustion engine. By summarizing various experimental results based on studies of three kinds of hole designs, the maximum error was 0.373 mm and the minimum error was 0.053 mm, which is within the general range of manufacturing tolerances (6 0.5 mm) used in engineering schematics. The second case examined the measurement of certain key dimensions of an aggregate truck bed, and the results showed that the measured difference between the three-dimensional method and automatic transformer observation system is less than 1.2%. The proposed three-dimensional measurement system is inexpensive, offers an easy set up, and provides a certain amount of accuracy and stability.
Machine-vision-based reading and sorting devices have been used to measure and classify items. Here, we extend their application to the sorting and assembling of items identified by their geometry and color. In this study, we developed an improved machine vision system that is capable of discerning and categorizing items of distinct geometries and colors and utilizes a computer-controlled robotic system to manipulate and segregate these items. Hence, a machine vision system for an automatic classification process while operating a robotic arm is hereby developed. To obtain positioning information, the proposed system uses cameras that were mounted above the working platform to acquire images. Perspective and quadratic transformations were used to transform the image coordinates of the calibration system to the world coordinates by using a calibration procedure. By these methods, the proposed system can ascertain the two-and three-dimensional coordinates of the objects and automatically perform classification and assembly operations using the data collected from the visual recognition system.
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