Automatic classification of legumes using leaf vein image features
In this paper, a procedure for segmenting and classifying scanned legume leaves based only on the analysis of their veins is proposed (leaf shape, size, texture and color are discarded). Three legume species are studied, namely soybean, red and white beans. The leaf images are acquired using a stand...
| Main Authors: | , , , , , |
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| Format: | Artículo |
| Language: | Inglés |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://www.sciencedirect.com/science/article/pii/S0031320313002641 http://hdl.handle.net/20.500.12123/2512 https://doi.org/10.1016/j.patcog.2013.06.012 |
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| author | Larese, Monica Graciela Namias, Rafael Craviotto, Roque Mario Arango, Miriam Raquel Gallo, Carina Del Valle Granitto, Pablo Miguel |
| author_browse | Arango, Miriam Raquel Craviotto, Roque Mario Gallo, Carina Del Valle Granitto, Pablo Miguel Larese, Monica Graciela Namias, Rafael |
| author_facet | Larese, Monica Graciela Namias, Rafael Craviotto, Roque Mario Arango, Miriam Raquel Gallo, Carina Del Valle Granitto, Pablo Miguel |
| author_sort | Larese, Monica Graciela |
| collection | INTA Digital |
| description | In this paper, a procedure for segmenting and classifying scanned legume leaves based only on the analysis of their veins is proposed (leaf shape, size, texture and color are discarded). Three legume species are studied, namely soybean, red and white beans. The leaf images are acquired using a standard scanner. The segmentation is performed using the unconstrained hit-or-miss transform and adaptive thresholding. Several morphological features are computed on the segmented venation, and classified using four alternative classifiers, namely support vector machines (linear and Gaussian kernels), penalized discriminant analysis and random forests. The performance is compared to the one obtained with cleared leaves images, which require a more expensive, time consuming and delicate procedure of acquisition. The results are encouraging, showing that the proposed approach is an effective and more economic alternative solution which outperforms the manual expert's recognition. |
| format | Artículo |
| id | INTA2512 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| record_format | dspace |
| spelling | INTA25122018-06-21T12:33:40Z Automatic classification of legumes using leaf vein image features Larese, Monica Graciela Namias, Rafael Craviotto, Roque Mario Arango, Miriam Raquel Gallo, Carina Del Valle Granitto, Pablo Miguel Leguminosas Nervaduras Foliares Análisis de Imágenes Legumes Leaf Veins Image Analysis In this paper, a procedure for segmenting and classifying scanned legume leaves based only on the analysis of their veins is proposed (leaf shape, size, texture and color are discarded). Three legume species are studied, namely soybean, red and white beans. The leaf images are acquired using a standard scanner. The segmentation is performed using the unconstrained hit-or-miss transform and adaptive thresholding. Several morphological features are computed on the segmented venation, and classified using four alternative classifiers, namely support vector machines (linear and Gaussian kernels), penalized discriminant analysis and random forests. The performance is compared to the one obtained with cleared leaves images, which require a more expensive, time consuming and delicate procedure of acquisition. The results are encouraging, showing that the proposed approach is an effective and more economic alternative solution which outperforms the manual expert's recognition. EEA Oliveros Fil: Larese, Monica Graciela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina Fil: Namias, Rafael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina Fil: Craviotto, Roque Mario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Arango, Miriam Raquel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Gallo, Carina Del Valle. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina Fil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina 2018-05-30T12:08:08Z 2018-05-30T12:08:08Z 2014-01 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://www.sciencedirect.com/science/article/pii/S0031320313002641 http://hdl.handle.net/20.500.12123/2512 0031-3203 https://doi.org/10.1016/j.patcog.2013.06.012 eng info:eu-repo/semantics/restrictedAccess application/pdf Pattern recognition 47 (1) : 158-168. (January 2014) |
| spellingShingle | Leguminosas Nervaduras Foliares Análisis de Imágenes Legumes Leaf Veins Image Analysis Larese, Monica Graciela Namias, Rafael Craviotto, Roque Mario Arango, Miriam Raquel Gallo, Carina Del Valle Granitto, Pablo Miguel Automatic classification of legumes using leaf vein image features |
| title | Automatic classification of legumes using leaf vein image features |
| title_full | Automatic classification of legumes using leaf vein image features |
| title_fullStr | Automatic classification of legumes using leaf vein image features |
| title_full_unstemmed | Automatic classification of legumes using leaf vein image features |
| title_short | Automatic classification of legumes using leaf vein image features |
| title_sort | automatic classification of legumes using leaf vein image features |
| topic | Leguminosas Nervaduras Foliares Análisis de Imágenes Legumes Leaf Veins Image Analysis |
| url | https://www.sciencedirect.com/science/article/pii/S0031320313002641 http://hdl.handle.net/20.500.12123/2512 https://doi.org/10.1016/j.patcog.2013.06.012 |
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