Natural Inspired Intelligent Visual Computing and Its Application to Viticulture
This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the devel...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-05-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/17/6/1186 |
| _version_ | 1817989802646044672 |
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| author | Li Minn Ang Kah Phooi Seng Feng Lu Ge |
| author_facet | Li Minn Ang Kah Phooi Seng Feng Lu Ge |
| author_sort | Li Minn Ang |
| collection | DOAJ |
| description | This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively. |
| first_indexed | 2024-04-14T00:51:39Z |
| format | Article |
| id | doaj.art-522737f3e1da4f83b455e729faf282a9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T00:51:39Z |
| publishDate | 2017-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-522737f3e1da4f83b455e729faf282a92022-12-22T02:21:47ZengMDPI AGSensors1424-82202017-05-01176118610.3390/s17061186s17061186Natural Inspired Intelligent Visual Computing and Its Application to ViticultureLi Minn Ang0Kah Phooi Seng1Feng Lu Ge2School of Computing & Mathematics, Charles Sturt University, Wagga Wagga 2678, AustraliaSchool of Computing & Mathematics, Charles Sturt University, Wagga Wagga 2678, AustraliaCM3 Research Centre, Charles Sturt University, Bathurst 2795, AustraliaThis paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively.http://www.mdpi.com/1424-8220/17/6/1186natural inspired computingintelligent systemartificial immune systemvisual information processingviticulture applications |
| spellingShingle | Li Minn Ang Kah Phooi Seng Feng Lu Ge Natural Inspired Intelligent Visual Computing and Its Application to Viticulture Sensors natural inspired computing intelligent system artificial immune system visual information processing viticulture applications |
| title | Natural Inspired Intelligent Visual Computing and Its Application to Viticulture |
| title_full | Natural Inspired Intelligent Visual Computing and Its Application to Viticulture |
| title_fullStr | Natural Inspired Intelligent Visual Computing and Its Application to Viticulture |
| title_full_unstemmed | Natural Inspired Intelligent Visual Computing and Its Application to Viticulture |
| title_short | Natural Inspired Intelligent Visual Computing and Its Application to Viticulture |
| title_sort | natural inspired intelligent visual computing and its application to viticulture |
| topic | natural inspired computing intelligent system artificial immune system visual information processing viticulture applications |
| url | http://www.mdpi.com/1424-8220/17/6/1186 |
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