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- Publisher Website: 10.1109/ICCASM.2010.5620820
- Scopus: eid_2-s2.0-78649587730
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Conference Paper: Study on fruit quality inspection based on color image processing
Title | Study on fruit quality inspection based on color image processing |
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Authors | |
Keywords | Fruit Quality Image Processing Inspection White Balance |
Issue Date | 2010 |
Citation | Iccasm 2010 - 2010 International Conference On Computer Application And System Modeling, Proceedings, 2010, v. 4, p. V41-V45 How to Cite? |
Abstract | In this paper, a new method of inspecting fruit quality is proposed based on color image processing. After an image of fruits is taken, white balance is performed. Then the image is transferred from the RGB color model to the HSI color model. Its simplified histograms of hue H and saturation S are calculated as the input of a designed BP network. The output of the BP network is the quality description of the inspected fruits. The number of neurons in the intermediate layer is optimized according to generated error of the BP network. After training, the quality of fruits is inspected by the BP network according to the simplified histograms of Hand S of their color image. Experiments are conducted with the quality inspection of bananas. Experiment results show the feasibility and reliability of proposed method. |
Persistent Identifier | http://hdl.handle.net/10722/158832 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, Y | en_US |
dc.contributor.author | Men, J | en_US |
dc.contributor.author | Cui, Y | en_US |
dc.contributor.author | Zhang, P | en_US |
dc.contributor.author | Chen, S | en_US |
dc.contributor.author | Huang, GQ | en_US |
dc.date.accessioned | 2012-08-08T09:03:31Z | - |
dc.date.available | 2012-08-08T09:03:31Z | - |
dc.date.issued | 2010 | en_US |
dc.identifier.citation | Iccasm 2010 - 2010 International Conference On Computer Application And System Modeling, Proceedings, 2010, v. 4, p. V41-V45 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/158832 | - |
dc.description.abstract | In this paper, a new method of inspecting fruit quality is proposed based on color image processing. After an image of fruits is taken, white balance is performed. Then the image is transferred from the RGB color model to the HSI color model. Its simplified histograms of hue H and saturation S are calculated as the input of a designed BP network. The output of the BP network is the quality description of the inspected fruits. The number of neurons in the intermediate layer is optimized according to generated error of the BP network. After training, the quality of fruits is inspected by the BP network according to the simplified histograms of Hand S of their color image. Experiments are conducted with the quality inspection of bananas. Experiment results show the feasibility and reliability of proposed method. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | ICCASM 2010 - 2010 International Conference on Computer Application and System Modeling, Proceedings | en_US |
dc.subject | Fruit Quality | en_US |
dc.subject | Image Processing | en_US |
dc.subject | Inspection | en_US |
dc.subject | White Balance | en_US |
dc.title | Study on fruit quality inspection based on color image processing | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Huang, GQ:gqhuang@hkucc.hku.hk | en_US |
dc.identifier.authority | Huang, GQ=rp00118 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1109/ICCASM.2010.5620820 | en_US |
dc.identifier.scopus | eid_2-s2.0-78649587730 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-78649587730&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.volume | 4 | en_US |
dc.identifier.spage | V41 | en_US |
dc.identifier.epage | V45 | en_US |
dc.identifier.scopusauthorid | Wang, Y=35293863000 | en_US |
dc.identifier.scopusauthorid | Men, J=36650882000 | en_US |
dc.identifier.scopusauthorid | Cui, Y=35331683800 | en_US |
dc.identifier.scopusauthorid | Zhang, P=35175258500 | en_US |
dc.identifier.scopusauthorid | Chen, S=35331828000 | en_US |
dc.identifier.scopusauthorid | Huang, GQ=7403425048 | en_US |