A Curvelet-SC Recognition Method for Maize Disease
Because the corn vein and noise influence the contour extraction of the maize leaf disease, we put forward a new recognition algorithm based on Curvelet and Shape Context (SC). This method can improve the speed and accuracy of maize leaf disease recognition. Firstly, we use Seeded Regional Growing (...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
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| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2015/164547 |
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| _version_ | 1832555064975163392 |
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| author | Jing Luo Shuze Geng Chunbo Xiu Dan Song Tingting Dong |
| author_facet | Jing Luo Shuze Geng Chunbo Xiu Dan Song Tingting Dong |
| author_sort | Jing Luo |
| collection | DOAJ |
| description | Because the corn vein and noise influence the contour extraction of the maize leaf disease, we put forward a new recognition algorithm based on Curvelet and Shape Context (SC). This method can improve the speed and accuracy of maize leaf disease recognition. Firstly, we use Seeded Regional Growing (SRG) algorithm to segment the maize leaf disease image. Secondly, Curvelet Modulus Correlation (CMC) method is put forward to extract the effective contour of maize leaf disease. Thirdly, we combine CMC with the SC algorithm to obtain the histogram features and then use these features we obtain to calculate the similarities between the template image and the target image. Finally, we adopt n-fold cross-validation algorithm to recognize diseases on maize leaf disease database. Experimental results show that the proposed algorithm can recognize 6 kinds of maize leaf diseases accurately and achieve the accuracy of 94.446%. Meanwhile this algorithm has guiding significance for other diseases recognition to an extent. |
| format | Article |
| id | doaj-art-aaf58d872e084e9cbba2e2b193fd5fe4 |
| institution | Kabale University |
| issn | 2090-0147 2090-0155 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Electrical and Computer Engineering |
| spelling | doaj-art-aaf58d872e084e9cbba2e2b193fd5fe42025-02-03T05:49:48ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552015-01-01201510.1155/2015/164547164547A Curvelet-SC Recognition Method for Maize DiseaseJing Luo0Shuze Geng1Chunbo Xiu2Dan Song3Tingting Dong4Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, ChinaKey Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, ChinaKey Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, ChinaKey Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, ChinaKey Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, ChinaBecause the corn vein and noise influence the contour extraction of the maize leaf disease, we put forward a new recognition algorithm based on Curvelet and Shape Context (SC). This method can improve the speed and accuracy of maize leaf disease recognition. Firstly, we use Seeded Regional Growing (SRG) algorithm to segment the maize leaf disease image. Secondly, Curvelet Modulus Correlation (CMC) method is put forward to extract the effective contour of maize leaf disease. Thirdly, we combine CMC with the SC algorithm to obtain the histogram features and then use these features we obtain to calculate the similarities between the template image and the target image. Finally, we adopt n-fold cross-validation algorithm to recognize diseases on maize leaf disease database. Experimental results show that the proposed algorithm can recognize 6 kinds of maize leaf diseases accurately and achieve the accuracy of 94.446%. Meanwhile this algorithm has guiding significance for other diseases recognition to an extent.http://dx.doi.org/10.1155/2015/164547 |
| spellingShingle | Jing Luo Shuze Geng Chunbo Xiu Dan Song Tingting Dong A Curvelet-SC Recognition Method for Maize Disease Journal of Electrical and Computer Engineering |
| title | A Curvelet-SC Recognition Method for Maize Disease |
| title_full | A Curvelet-SC Recognition Method for Maize Disease |
| title_fullStr | A Curvelet-SC Recognition Method for Maize Disease |
| title_full_unstemmed | A Curvelet-SC Recognition Method for Maize Disease |
| title_short | A Curvelet-SC Recognition Method for Maize Disease |
| title_sort | curvelet sc recognition method for maize disease |
| url | http://dx.doi.org/10.1155/2015/164547 |
| work_keys_str_mv | AT jingluo acurveletscrecognitionmethodformaizedisease AT shuzegeng acurveletscrecognitionmethodformaizedisease AT chunboxiu acurveletscrecognitionmethodformaizedisease AT dansong acurveletscrecognitionmethodformaizedisease AT tingtingdong acurveletscrecognitionmethodformaizedisease AT jingluo curveletscrecognitionmethodformaizedisease AT shuzegeng curveletscrecognitionmethodformaizedisease AT chunboxiu curveletscrecognitionmethodformaizedisease AT dansong curveletscrecognitionmethodformaizedisease AT tingtingdong curveletscrecognitionmethodformaizedisease |