Cargando…

Discriminant WSRC for Large-Scale Plant Species Recognition

In sparse representation based classification (SRC) and weighted SRC (WSRC), it is time-consuming to solve the global sparse representation problem. A discriminant WSRC (DWSRC) is proposed for large-scale plant species recognition, including two stages. Firstly, several subdictionaries are construct...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Shanwen, Zhang, Chuanlei, Zhu, Yihai, You, Zhuhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5757167/
https://www.ncbi.nlm.nih.gov/pubmed/29434636
http://dx.doi.org/10.1155/2017/9581292
_version_ 1783290817548386304
author Zhang, Shanwen
Zhang, Chuanlei
Zhu, Yihai
You, Zhuhong
author_facet Zhang, Shanwen
Zhang, Chuanlei
Zhu, Yihai
You, Zhuhong
author_sort Zhang, Shanwen
collection PubMed
description In sparse representation based classification (SRC) and weighted SRC (WSRC), it is time-consuming to solve the global sparse representation problem. A discriminant WSRC (DWSRC) is proposed for large-scale plant species recognition, including two stages. Firstly, several subdictionaries are constructed by dividing the dataset into several similar classes, and a subdictionary is chosen by the maximum similarity between the test sample and the typical sample of each similar class. Secondly, the weighted sparse representation of the test image is calculated with respect to the chosen subdictionary, and then the leaf category is assigned through the minimum reconstruction error. Different from the traditional SRC and its improved approaches, we sparsely represent the test sample on a subdictionary whose base elements are the training samples of the selected similar class, instead of using the generic overcomplete dictionary on the entire training samples. Thus, the complexity to solving the sparse representation problem is reduced. Moreover, DWSRC is adapted to newly added leaf species without rebuilding the dictionary. Experimental results on the ICL plant leaf database show that the method has low computational complexity and high recognition rate and can be clearly interpreted.
format Online
Article
Text
id pubmed-5757167
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-57571672018-02-12 Discriminant WSRC for Large-Scale Plant Species Recognition Zhang, Shanwen Zhang, Chuanlei Zhu, Yihai You, Zhuhong Comput Intell Neurosci Research Article In sparse representation based classification (SRC) and weighted SRC (WSRC), it is time-consuming to solve the global sparse representation problem. A discriminant WSRC (DWSRC) is proposed for large-scale plant species recognition, including two stages. Firstly, several subdictionaries are constructed by dividing the dataset into several similar classes, and a subdictionary is chosen by the maximum similarity between the test sample and the typical sample of each similar class. Secondly, the weighted sparse representation of the test image is calculated with respect to the chosen subdictionary, and then the leaf category is assigned through the minimum reconstruction error. Different from the traditional SRC and its improved approaches, we sparsely represent the test sample on a subdictionary whose base elements are the training samples of the selected similar class, instead of using the generic overcomplete dictionary on the entire training samples. Thus, the complexity to solving the sparse representation problem is reduced. Moreover, DWSRC is adapted to newly added leaf species without rebuilding the dictionary. Experimental results on the ICL plant leaf database show that the method has low computational complexity and high recognition rate and can be clearly interpreted. Hindawi 2017 2017-12-25 /pmc/articles/PMC5757167/ /pubmed/29434636 http://dx.doi.org/10.1155/2017/9581292 Text en Copyright © 2017 Shanwen Zhang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhang, Shanwen
Zhang, Chuanlei
Zhu, Yihai
You, Zhuhong
Discriminant WSRC for Large-Scale Plant Species Recognition
title Discriminant WSRC for Large-Scale Plant Species Recognition
title_full Discriminant WSRC for Large-Scale Plant Species Recognition
title_fullStr Discriminant WSRC for Large-Scale Plant Species Recognition
title_full_unstemmed Discriminant WSRC for Large-Scale Plant Species Recognition
title_short Discriminant WSRC for Large-Scale Plant Species Recognition
title_sort discriminant wsrc for large-scale plant species recognition
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5757167/
https://www.ncbi.nlm.nih.gov/pubmed/29434636
http://dx.doi.org/10.1155/2017/9581292
work_keys_str_mv AT zhangshanwen discriminantwsrcforlargescaleplantspeciesrecognition
AT zhangchuanlei discriminantwsrcforlargescaleplantspeciesrecognition
AT zhuyihai discriminantwsrcforlargescaleplantspeciesrecognition
AT youzhuhong discriminantwsrcforlargescaleplantspeciesrecognition