Development of a Color Object Classification and Measurement System Using Machine Vision

Abstract

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.

The Research on the Motion Control of the Sorting Manipulator based on Machine Vision

“…The manipulator plays an important role in the field of automation engineering as an important component of industrial systems [24]. A study has developed an improved machine vision system that is capable of identifying and classifying items with different geometric shapes and colors and manipulating and separating them using a computercontrolled manipulator [25]. The experimental parameters in this paper differed from those in existing studies in the following aspects: (1) existing experiments use three cameras, while this paper used two cameras; (2) the sorted objects in existing research are in a condition of rest, while the sorted objects in this paper are in a state of motion; (3) existing research on manipulators under machine vision is oriented to grasp and sort items according to different geometric shapes and colors, but this paper took into account not only the different geometric shapes of the items, but also the different running speeds of the items on the conveyor belt and the complexity of the environment in which the manipulator performs sorting.…”

Automated Defect Inspection Algorithm Incorporated Spectral-Domain Optical Coherence Tomography for Optical Polarizing Thin Films

“…Quality inspection of industrial products have been mostly succeeded using non-destructive and non-contact techniques incorporated with automated image processing and analysis. Visual inspection methods, machine vision with a charge-coupled device (CCD) camera-based inspection or electronic inspection have been frequently employed for the quality inspection in optical thin film industry [3,4]. Since these techniques provide information of top surface information, highly penetrating X-ray and computed tomographic techniques were considered for sub-surface, but none of them provides depth resolution at the micro-meter scale [5,6].…”