Image preprocessing using quick color averaging approach for color machine vision (CMV) systems
College
Gokongwei College of Engineering
Department/Unit
Manufacturing Engineering and Management
Document Type
Conference Proceeding
Source Title
HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management
Volume
2018-January
First Page
1
Last Page
4
Publication Date
7-2-2017
Abstract
Image preprocessing is a preceding technique that an image undergoes before being subject to a main process. This is necessary since most unprocessed images are hard and sometimes impractical to manipulate. A color machine vision (CMV) system is an application where colors of a certain image is used with vision techniques. Some CMV applications in the industry include inspection, sorting, indication, detection, and measuring. However, CMV has limitations like proper lighting, camera calibration, etc. Due to its limitations, preprocessing techniques are essential to its success. With that, this paper proposed the application of quick color averaging as an image preprocessing technique for CMV applications. Color averaging is the process of changing the color values of the pixels of an image contour to the mean color value of all the pixels in the contour. From the results, this study concluded that color averaging using vision techniques is viable for image preprocessing in machine vision. Recommendations for future studies that may improve the color averaging process were also suggested. © 2017 IEEE.
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Digitial Object Identifier (DOI)
10.1109/HNICEM.2017.8269475
Recommended Citation
Luta, R. G., Baldovino, R. G., & Bugtai, N. T. (2017). Image preprocessing using quick color averaging approach for color machine vision (CMV) systems. HNICEM 2017 - 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, 2018-January, 1-4. https://doi.org/10.1109/HNICEM.2017.8269475
Disciplines
Mechanical Engineering
Keywords
Computer vision; Image processing; Color vision
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