Method of Ear Detection for Maize Seed Based on Fisher Criterion
The purpose of this paper is to use machine vision to detect the size, shape, texture and color of maize seed ear. The traditional method is very limited and cannot meet the detection efficiency. This paper used logistic regression linear discriminant analysis method, the rule of perceptron, Fisher...
| Format: | Article |
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| Language: | zho |
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EDP Sciences
2018-04-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/pdf/2018/02/jnwpu2018362p332.pdf |
| _version_ | 1797669082059767808 |
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| collection | DOAJ |
| description | The purpose of this paper is to use machine vision to detect the size, shape, texture and color of maize seed ear. The traditional method is very limited and cannot meet the detection efficiency. This paper used logistic regression linear discriminant analysis method, the rule of perceptron, Fisher method and the least-square method, this paper use change between the Fisher criterion according to the the class of discrete degree error matrix and matrix of the discrete degree of reconstruction error in class than the maximum projection direction, classifying clusters. By fusion Fisher discriminant analysis method for testing in the test, through a large number of experiments and comparison method, the experiment proved that Fisher can high efficiency and high precision of classifying seed corn ear detection. |
| first_indexed | 2024-03-11T20:39:07Z |
| format | Article |
| id | doaj.art-336614041d1d4d9ba95e480acb20e55d |
| institution | Directory Open Access Journal |
| issn | 1000-2758 2609-7125 |
| language | zho |
| last_indexed | 2024-03-11T20:39:07Z |
| publishDate | 2018-04-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Xibei Gongye Daxue Xuebao |
| spelling | doaj.art-336614041d1d4d9ba95e480acb20e55d2023-10-02T04:08:28ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252018-04-0136233233810.1051/jnwpu/20183620332jnwpu2018362p332Method of Ear Detection for Maize Seed Based on Fisher Criterion01School of Automation, Northwestern Polytechnical UniversitySchool of Marine Science and Technology, Northwestern Polytechnical UniversityThe purpose of this paper is to use machine vision to detect the size, shape, texture and color of maize seed ear. The traditional method is very limited and cannot meet the detection efficiency. This paper used logistic regression linear discriminant analysis method, the rule of perceptron, Fisher method and the least-square method, this paper use change between the Fisher criterion according to the the class of discrete degree error matrix and matrix of the discrete degree of reconstruction error in class than the maximum projection direction, classifying clusters. By fusion Fisher discriminant analysis method for testing in the test, through a large number of experiments and comparison method, the experiment proved that Fisher can high efficiency and high precision of classifying seed corn ear detection.https://www.jnwpu.org/articles/jnwpu/pdf/2018/02/jnwpu2018362p332.pdfmachine visiondetection efficiencydiscriminant analysis methodprojection directionfisher discriminant |
| spellingShingle | Method of Ear Detection for Maize Seed Based on Fisher Criterion Xibei Gongye Daxue Xuebao machine vision detection efficiency discriminant analysis method projection direction fisher discriminant |
| title | Method of Ear Detection for Maize Seed Based on Fisher Criterion |
| title_full | Method of Ear Detection for Maize Seed Based on Fisher Criterion |
| title_fullStr | Method of Ear Detection for Maize Seed Based on Fisher Criterion |
| title_full_unstemmed | Method of Ear Detection for Maize Seed Based on Fisher Criterion |
| title_short | Method of Ear Detection for Maize Seed Based on Fisher Criterion |
| title_sort | method of ear detection for maize seed based on fisher criterion |
| topic | machine vision detection efficiency discriminant analysis method projection direction fisher discriminant |
| url | https://www.jnwpu.org/articles/jnwpu/pdf/2018/02/jnwpu2018362p332.pdf |