Plant Leaf Recognition through Local Discriminative Tangent Space Alignment
Manifold learning based dimensionality reduction algorithms have been payed much attention in plant leaf recognition as the algorithms can select a subset of effective and efficient discriminative features in the leaf images. In this paper, a dimensionality reduction method based on local discrimina...
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Format: | Article |
Language: | English |
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Wiley
2016-01-01
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Series: | Journal of Electrical and Computer Engineering |
Online Access: | http://dx.doi.org/10.1155/2016/1989485 |
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author | Chuanlei Zhang Shanwen Zhang Weidong Fang |
author_facet | Chuanlei Zhang Shanwen Zhang Weidong Fang |
author_sort | Chuanlei Zhang |
collection | DOAJ |
description | Manifold learning based dimensionality reduction algorithms have been payed much attention in plant leaf recognition as the algorithms can select a subset of effective and efficient discriminative features in the leaf images. In this paper, a dimensionality reduction method based on local discriminative tangent space alignment (LDTSA) is introduced for plant leaf recognition based on leaf images. The proposed method can embrace part optimization and whole alignment and encapsulate the geometric and discriminative information into a local patch. The experiments on two plant leaf databases, ICL and Swedish plant leaf datasets, demonstrate the effectiveness and feasibility of the proposed method. |
format | Article |
id | doaj-art-40ec3bd45bc14b4b9bf6f95183adc2b6 |
institution | Kabale University |
issn | 2090-0147 2090-0155 |
language | English |
publishDate | 2016-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Electrical and Computer Engineering |
spelling | doaj-art-40ec3bd45bc14b4b9bf6f95183adc2b62025-02-03T01:28:09ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552016-01-01201610.1155/2016/19894851989485Plant Leaf Recognition through Local Discriminative Tangent Space AlignmentChuanlei Zhang0Shanwen Zhang1Weidong Fang2School of Science and Information Engineering, Tianjin University of Science and Technology, Tianjin 300222, ChinaDepartment of Electronics and Information Engineering, Xijing University, Xi’an 710123, ChinaKey Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai 200444, ChinaManifold learning based dimensionality reduction algorithms have been payed much attention in plant leaf recognition as the algorithms can select a subset of effective and efficient discriminative features in the leaf images. In this paper, a dimensionality reduction method based on local discriminative tangent space alignment (LDTSA) is introduced for plant leaf recognition based on leaf images. The proposed method can embrace part optimization and whole alignment and encapsulate the geometric and discriminative information into a local patch. The experiments on two plant leaf databases, ICL and Swedish plant leaf datasets, demonstrate the effectiveness and feasibility of the proposed method.http://dx.doi.org/10.1155/2016/1989485 |
spellingShingle | Chuanlei Zhang Shanwen Zhang Weidong Fang Plant Leaf Recognition through Local Discriminative Tangent Space Alignment Journal of Electrical and Computer Engineering |
title | Plant Leaf Recognition through Local Discriminative Tangent Space Alignment |
title_full | Plant Leaf Recognition through Local Discriminative Tangent Space Alignment |
title_fullStr | Plant Leaf Recognition through Local Discriminative Tangent Space Alignment |
title_full_unstemmed | Plant Leaf Recognition through Local Discriminative Tangent Space Alignment |
title_short | Plant Leaf Recognition through Local Discriminative Tangent Space Alignment |
title_sort | plant leaf recognition through local discriminative tangent space alignment |
url | http://dx.doi.org/10.1155/2016/1989485 |
work_keys_str_mv | AT chuanleizhang plantleafrecognitionthroughlocaldiscriminativetangentspacealignment AT shanwenzhang plantleafrecognitionthroughlocaldiscriminativetangentspacealignment AT weidongfang plantleafrecognitionthroughlocaldiscriminativetangentspacealignment |