A NOVEL METHOD FOR INSPECTION DEFECTS IN COMMERCIAL EGGS USING COMPUTER VISION
The objective of this work is to compare the use of classical image processing approaches with deep learning approaches in a visual inspection system for defects in commercial eggs. Currently, many industries perform the detection of defects in eggs manually, this implies a large number of workers w...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2021-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2021/809/2021/isprs-archives-XLIII-B2-2021-809-2021.pdf |
| Summary: | The objective of this work is to compare the use of classical image processing approaches with deep learning approaches in a visual inspection system for defects in commercial eggs. Currently, many industries perform the detection of defects in eggs manually, this implies a large number of workers with long working hours who are exposed to visual fatigue and physical and mental discomfort. As a solution, this work proposes to develop an automatic inspection technique for defects in eggs using computer vision, capable of being operable in the industry. Different image processing approaches were evaluated in order to determine the best solution in terms of performance and processing time. |
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| ISSN: | 1682-1750 2194-9034 |