| Paper Abstract and Keywords |
| Presentation |
2006-10-20 16:15
Lawn weeds detection methods using image processing techniques
Ukrit Watchareeruetai, Yoshinori Takeuchi, Tetsuya Matsumoto, Hiroaki Kudo, Noboru Ohnishi (Nagoya Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In this work, three methods of lawn weeds detection based on various image processing techniques, Bayesian classifier, morphology operators, and gray-scale uniformity analysis based methods, were evaluated and compared by using four different seasons image datasets. In the evaluations, two types of automatic weeding systems (i.e., chemical and non-chemical based) together with the detection methods were simulated and their performances were compared. From the results, for chemical approach, the Bayesian classifier based method could destroy 80.85%-96.30% of weeds, with more than 80% of accuracy for all datasets. For non-chemical approach, its accuracy was nearly 100% for all datasets. This shows its robustness against changing in season. The morphological operator based method was the best in weeds destruction for the non-chemical based system. However, its accuracy performance ranked as the last. For gray-scale uniformity analysis method, it missed detecting a lot of weeds for winter dataset, only 31.91%-36.17% of total weeds could be destroyed. Among three detection methods, the Bayesian classifier based method can be considered as the most appropriate method for both chemical and non-chemical weeding systems. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
lawn / weed detection / Bayesian classifier / morphology operator / gray-scale uniformity analysis / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 106, no. 301, PRMU2006-115, pp. 65-70, Oct. 2006. |
| Paper # |
PRMU2006-115 |
| Date of Issue |
2006-10-13 (PRMU) |
| ISSN |
Print edition: ISSN 0913-5685 |
| Download PDF |
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| Conference Information |
| Committee |
PRMU NLC TL |
| Conference Date |
2006-10-19 - 2006-10-20 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
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| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
PRMU |
| Conference Code |
2006-10-PRMU-NLC-TL |
| Language |
English |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Lawn weeds detection methods using image processing techniques |
| Sub Title (in English) |
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| Keyword(1) |
lawn |
| Keyword(2) |
weed detection |
| Keyword(3) |
Bayesian classifier |
| Keyword(4) |
morphology operator |
| Keyword(5) |
gray-scale uniformity analysis |
| Keyword(6) |
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| Keyword(7) |
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| 1st Author's Name |
Ukrit Watchareeruetai |
| 1st Author's Affiliation |
Nagoya University (Nagoya Univ.) |
| 2nd Author's Name |
Yoshinori Takeuchi |
| 2nd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
| 3rd Author's Name |
Tetsuya Matsumoto |
| 3rd Author's Affiliation |
Nagoya University (Nagoya Univ.) |
| 4th Author's Name |
Hiroaki Kudo |
| 4th Author's Affiliation |
Nagoya University (Nagoya Univ.) |
| 5th Author's Name |
Noboru Ohnishi |
| 5th Author's Affiliation |
Nagoya University (Nagoya Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2006-10-20 16:15:00 |
| Presentation Time |
30 minutes |
| Registration for |
PRMU |
| Paper # |
PRMU2006-115 |
| Volume (vol) |
vol.106 |
| Number (no) |
no.301 |
| Page |
pp.65-70 |
| #Pages |
6 |
| Date of Issue |
2006-10-13 (PRMU) |
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