A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits
Nondestructive inspection technology based on machine vision can effectively improve the efficiency of fresh fruit quality inspection. However, fruits with smooth skin and less texture are easily affected by specular highlights during the image acquisition, resulting in light spots appearing on the...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-07-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/13/3215 |
| _version_ | 1797433994068885504 |
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| author | Jinglei Hao Yongqiang Zhao Qunnie Peng |
| author_facet | Jinglei Hao Yongqiang Zhao Qunnie Peng |
| author_sort | Jinglei Hao |
| collection | DOAJ |
| description | Nondestructive inspection technology based on machine vision can effectively improve the efficiency of fresh fruit quality inspection. However, fruits with smooth skin and less texture are easily affected by specular highlights during the image acquisition, resulting in light spots appearing on the surface of fruits, which severely affects the subsequent quality inspection. Aiming at this issue, we propose a new specular highlight removal algorithm based on multi-band polarization imaging. First of all, we realize real-time image acquisition by designing a new multi-band polarization imager, which can acquire all the spectral and polarization information through single image capture. Then we propose a joint multi-band-polarization characteristic vector constraint to realize the detection of specular highlight, and next we put forward a Max-Min multi-band-polarization differencing scheme combined with an ergodic least-squares separation for specular highlight removal, and finally, the chromaticity consistency regularization is used to compensate the missing details. Experimental results demonstrate that the proposed algorithm can effectively and stably remove the specular highlight and provide more accurate information for subsequent fruit quality inspection. Besides, the comparison of algorithm speed further shows that our proposed algorithm has a good tradeoff between accuracy and complexity. |
| first_indexed | 2024-03-09T10:24:55Z |
| format | Article |
| id | doaj.art-133b360a432045589105056897940592 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T10:24:55Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-133b360a4320455891050568979405922023-12-01T21:41:08ZengMDPI AGRemote Sensing2072-42922022-07-011413321510.3390/rs14133215A Specular Highlight Removal Algorithm for Quality Inspection of Fresh FruitsJinglei Hao0Yongqiang Zhao1Qunnie Peng2School of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaScience and Technology on Electro-Optic Control Laboratory, Luoyang 471000, ChinaNondestructive inspection technology based on machine vision can effectively improve the efficiency of fresh fruit quality inspection. However, fruits with smooth skin and less texture are easily affected by specular highlights during the image acquisition, resulting in light spots appearing on the surface of fruits, which severely affects the subsequent quality inspection. Aiming at this issue, we propose a new specular highlight removal algorithm based on multi-band polarization imaging. First of all, we realize real-time image acquisition by designing a new multi-band polarization imager, which can acquire all the spectral and polarization information through single image capture. Then we propose a joint multi-band-polarization characteristic vector constraint to realize the detection of specular highlight, and next we put forward a Max-Min multi-band-polarization differencing scheme combined with an ergodic least-squares separation for specular highlight removal, and finally, the chromaticity consistency regularization is used to compensate the missing details. Experimental results demonstrate that the proposed algorithm can effectively and stably remove the specular highlight and provide more accurate information for subsequent fruit quality inspection. Besides, the comparison of algorithm speed further shows that our proposed algorithm has a good tradeoff between accuracy and complexity.https://www.mdpi.com/2072-4292/14/13/3215specular highlight removalmulti-band polarization imagingimaging processingnondestructive inspection technologyquality inspection of fresh fruitsmachine vision |
| spellingShingle | Jinglei Hao Yongqiang Zhao Qunnie Peng A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits Remote Sensing specular highlight removal multi-band polarization imaging imaging processing nondestructive inspection technology quality inspection of fresh fruits machine vision |
| title | A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits |
| title_full | A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits |
| title_fullStr | A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits |
| title_full_unstemmed | A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits |
| title_short | A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits |
| title_sort | specular highlight removal algorithm for quality inspection of fresh fruits |
| topic | specular highlight removal multi-band polarization imaging imaging processing nondestructive inspection technology quality inspection of fresh fruits machine vision |
| url | https://www.mdpi.com/2072-4292/14/13/3215 |
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