Computer Vision-Based System for Classification and Sorting Color Objects
Open accessAbstract
Interest in computer vision has grown considerably in industrial applications of robotic arms such as packaging, sorting, and other applications. The real challenge is how to improve the current sorting system based on image processing in the four-points to identify, manipulate, select and sort objects depending on color and geometry. This paper presents a mechatronic sorting system with the application of image processing using a web camera by sensing existing parts and capturing them in real-time, then defining colors and analyzing geometric data. This information is processed for the handling mechanism. A robotic arm has 5 DOF is used in sorting the objects have different geometries (circle, rectangular, and triangle) and a different color (red, green, blue, brown, orange, and cyan). The project deals with an automated material handling system. It aims to classify color objects by color, size, and geometry, which comes on a conveyor belt by selecting and placing the parts in their pre-programmed location. Image processing is applied in EmguCV and visual studio software. An image is a matrix of pixels, image processing is the processes applied on image to convert it into digital form and implement some process on it to improve an image. The Canny edge detection algorithm is used for shape identification in image processing. A microcontroller with computer vision is used to automate the sorting process. Experimental results reveal the effectiveness, high accuracy and low cost of computer vision with a robotic arm in the sorting process according to color and shape.
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A computer vision-based robotic sorter can simultaneously detect and sort objects by colour and height, with sorting efficiency around 99%.
“In the proposed system, colour and height sorting efficiency is around 99%.”
From Advanced Applications of Industrial Robotics: New Trends and Possibilities (2021) · cites this paper as [53]
The Results and Discussion section says the robotic system sorts objects by colour and geometry, while Camera Calibration says it measures height to calculate dimensions—not that it sorts by height. The Conclusion reports 100% sorting accuracy, rather than around 99% efficiency. (LLM, conf=0.88)
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Research works printed but not linked: 9
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- Kurka P R G and Salazar A A D, 2019 "Applications of image processing in robotics and instrumentation", Mechanical Systems and Signal Processing, Vol. 124, pp. 142-169.
- Wang Z, Li H, and Zhang X, 2019 "Construction waste recycling robot for nails and screws: Computer vision technology and neural network approach", Automation in Construction, Vol. 978, pp. 220-228.
- Tiwari M, Lamba S S, and Gupta B, 2018 "An image processing and computer vision framework for efficient robotic sketching", International Conference on Robotics and Smart Manufacturing, Procedia Computer Science, Vol. 133, pp. 284-289, Kazakhstan.
- Cunha J, Ferreira R, and Lau N, 2015 "Computer vision and robotic manipulation for automated feeding of cork Drillers", Materials and Design, Vol. 82, pp. 290-296.
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Cited by
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Advanced Applications of Industrial Robotics: New Trends and Possibilities
Dzedzickis, A., Subačiūtė-Žemaitienė, J., Šutinys, E., Samukaitė-Bubnienė, U., & Bučinskas, V. (2021) · Applied Sciences · doi:10.3390/app12010135 · Cited by 228 · see citing works
- Authors
- Fadhil, A. T., Abbar, K. A., & Qusay, A. M.
- Affiliations
- University of Technology - Iraq (IQ)
- Venue
- IOP Conference Series: Materials Science and Engineering
- Publisher
- IOP Publishing
- Published
- 2020-02-01
- Volume
- 745
- Issue
- 1
- Pages
- 012030
- ISSN
- 1757-8981 (ISSN-L)
- 1757-899X
- OpenAlex
- W3012713317
- Cited by
- 11
- References
- 0
- Citations by year
- 2026: 2 · 2024: 4 · 2023: 2 · 2022: 2 · 2021: 1
- FWCI
- 1.76
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- IOP Conference Series Materials Science and Engineering (publishedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Engineering › Control and Systems Engineering › Robot Manipulation and Learning
- Physical Sciences › Engineering › Control and Systems Engineering › Industrial Automation and Control Systems
- Keywords
- robot manipulators, computer vision, image processing, Canny edge detection, shape recognition, automated material handling, conveyor belt, microcontroller, EmguCV, real-time object classification
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