Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties
This research is aimed at evaluating the texture and shape features using the most commonly used neural network architectures for cereal grain classification. An evaluation of the classification accuracy of texture and shape features and neural network was done to classify four Paddy (rice) grains,...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Engineering |
| Online Access: | http://dx.doi.org/10.1155/2014/617263 |
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| _version_ | 1841524884027473920 |
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| author | Archana Chaugule Suresh N. Mali |
| author_facet | Archana Chaugule Suresh N. Mali |
| author_sort | Archana Chaugule |
| collection | DOAJ |
| description | This research is aimed at evaluating the texture and shape features using the most commonly used neural network architectures for cereal grain classification. An evaluation of the classification accuracy of texture and shape features and neural network was done to classify four Paddy (rice) grains, namely, Karjat-6(K6), Ratnagiri-2(R2), Ratnagiri-4(R4), and Ratnagiri-24(R24). Algorithms were written to extract the features from the high-resolution images of kernels of four grain types and used as input features for classification. Different feature models were tested for their ability to classify these cereal grains. Effect of using different parameters on the accuracy of classification was studied. The most suitable feature from the features for accurate classification was identified. The shape feature set outperformed the texture feature set in almost all the instances of classification. |
| format | Article |
| id | doaj-art-ad9708771223468db436988ad57f7a06 |
| institution | Kabale University |
| issn | 2314-4904 2314-4912 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Engineering |
| spelling | doaj-art-ad9708771223468db436988ad57f7a062025-02-03T05:47:15ZengWileyJournal of Engineering2314-49042314-49122014-01-01201410.1155/2014/617263617263Evaluation of Texture and Shape Features for Classification of Four Paddy VarietiesArchana Chaugule0Suresh N. Mali1DYPIET, Pimpri, Pune 411017, IndiaDYPIET, Pimpri, Pune 411017, IndiaThis research is aimed at evaluating the texture and shape features using the most commonly used neural network architectures for cereal grain classification. An evaluation of the classification accuracy of texture and shape features and neural network was done to classify four Paddy (rice) grains, namely, Karjat-6(K6), Ratnagiri-2(R2), Ratnagiri-4(R4), and Ratnagiri-24(R24). Algorithms were written to extract the features from the high-resolution images of kernels of four grain types and used as input features for classification. Different feature models were tested for their ability to classify these cereal grains. Effect of using different parameters on the accuracy of classification was studied. The most suitable feature from the features for accurate classification was identified. The shape feature set outperformed the texture feature set in almost all the instances of classification.http://dx.doi.org/10.1155/2014/617263 |
| spellingShingle | Archana Chaugule Suresh N. Mali Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties Journal of Engineering |
| title | Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties |
| title_full | Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties |
| title_fullStr | Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties |
| title_full_unstemmed | Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties |
| title_short | Evaluation of Texture and Shape Features for Classification of Four Paddy Varieties |
| title_sort | evaluation of texture and shape features for classification of four paddy varieties |
| url | http://dx.doi.org/10.1155/2014/617263 |
| work_keys_str_mv | AT archanachaugule evaluationoftextureandshapefeaturesforclassificationoffourpaddyvarieties AT sureshnmali evaluationoftextureandshapefeaturesforclassificationoffourpaddyvarieties |