Image processing methods to evaluate tomato and zucchini damage in post-harvest stages
Through the supply chain, the quality or quality change of the products can generate important losses. The quality control in some steps is made manually that supposes a high level of subjectivity, controlling the quality and its evolution using automatic systems can suppose a reduction of the losse...
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Veröffentlicht in: | International journal of agricultural and biological engineering 2017-09, Vol.10 (5), p.126-133 |
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creator | Alvarez-Bermejo, Jos Antonio Giagnocavo, Cynthia Ming, Li Castillo Morales, Encarnaci髇 P. Morales Santos, Diego Xinting, Yang |
description | Through the supply chain, the quality or quality change of the products can generate important losses. The quality control in some steps is made manually that supposes a high level of subjectivity, controlling the quality and its evolution using automatic systems can suppose a reduction of the losses. Testing some automatic image analysis techniques in the case of tomatoes and zucchini is the main objective of this study. Two steps in the supply chain are considered, the feeding of the raw products into the handling chain (because low quality generates a reduction of the chain productivity) and the cool storage of the processed products (as the value at the market is reduced). It was proposed to analyze the incoming products at the head the processing line using CCD cameras to detect low quality and/or dirty products (corresponding to specific farmers/suppliers, it should be asked to improve to maintain the productivity of the line). The second stage is analyzing the evolution of the products along the cool chain (storage and transport), the use of an App developed to be use under Android was proposed to substitute the "visual" evaluation used in practice. The algorithms used, including stages of pre-treatment, segmentation, analysis and presentation of the results take account of the short time available and the limited capacity of the batteries. High performance techniques were applied to the homography stage to discard some of the images, resulting in better performance. Also threads and renderscript kernels were created to parallelize the methods used on the resulting images being able to inspect faster the products. The proposed method achieves success rates comparable to, and improving, the expert inspection. |
doi_str_mv | 10.25165/j.ijabe.20171005.3087 |
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Morales Santos, Diego ; Xinting, Yang</creator><creatorcontrib>Alvarez-Bermejo, Jos Antonio ; Giagnocavo, Cynthia ; Ming, Li ; Castillo Morales, Encarnaci髇 ; P. Morales Santos, Diego ; Xinting, Yang ; 2. C醫edra (Chair) Coexphal-UAL of Horticulture, Cooperative Studies and Sustainable Development, University of Almer韆, Spain ; 1. Department of Informatics, CeiA3, University of Almeria, Almeria, CP 04120, Spain ; 4. Department of Electronics and Computer Technology, Facultad de Ciencias, Granada, CP 18071, Spain ; 3. Beijing Research Center for Information Technology in Agriculture/National Engineering Research Center for Information Technology in Agriculture/National Engineering Laboratory for Agri-product Quality Traceability/Key Laboratory for Information Technologies in Agriculture, Ministry of Agriculture, Beijing 100097, China</creatorcontrib><description>Through the supply chain, the quality or quality change of the products can generate important losses. The quality control in some steps is made manually that supposes a high level of subjectivity, controlling the quality and its evolution using automatic systems can suppose a reduction of the losses. Testing some automatic image analysis techniques in the case of tomatoes and zucchini is the main objective of this study. Two steps in the supply chain are considered, the feeding of the raw products into the handling chain (because low quality generates a reduction of the chain productivity) and the cool storage of the processed products (as the value at the market is reduced). It was proposed to analyze the incoming products at the head the processing line using CCD cameras to detect low quality and/or dirty products (corresponding to specific farmers/suppliers, it should be asked to improve to maintain the productivity of the line). The second stage is analyzing the evolution of the products along the cool chain (storage and transport), the use of an App developed to be use under Android was proposed to substitute the "visual" evaluation used in practice. The algorithms used, including stages of pre-treatment, segmentation, analysis and presentation of the results take account of the short time available and the limited capacity of the batteries. High performance techniques were applied to the homography stage to discard some of the images, resulting in better performance. Also threads and renderscript kernels were created to parallelize the methods used on the resulting images being able to inspect faster the products. The proposed method achieves success rates comparable to, and improving, the expert inspection.</description><identifier>ISSN: 1934-6344</identifier><identifier>EISSN: 1934-6352</identifier><identifier>DOI: 10.25165/j.ijabe.20171005.3087</identifier><language>eng</language><publisher>Beijing: International Journal of Agricultural and Biological Engineering (IJABE)</publisher><subject>Automatic control ; Cameras ; CCD cameras ; Damage assessment ; Evolution ; Fruits ; Image analysis ; Image processing ; Image segmentation ; Inspection ; Kernels ; Parallel processing ; Pretreatment ; Productivity ; Quality control ; Reduction ; Smartphones ; Storage ; Supply chains ; Tomatoes ; Vision systems</subject><ispartof>International journal of agricultural and biological engineering, 2017-09, Vol.10 (5), p.126-133</ispartof><rights>Copyright International Journal of Agricultural and Biological Engineering (IJABE) Sep 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c283t-37a9b7f332de59deb378e22e6b6dac343517a456308afe7298b4392c5d311c8d3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,27901,27902</link.rule.ids></links><search><creatorcontrib>Alvarez-Bermejo, Jos Antonio</creatorcontrib><creatorcontrib>Giagnocavo, Cynthia</creatorcontrib><creatorcontrib>Ming, Li</creatorcontrib><creatorcontrib>Castillo Morales, Encarnaci髇</creatorcontrib><creatorcontrib>P. Morales Santos, Diego</creatorcontrib><creatorcontrib>Xinting, Yang</creatorcontrib><creatorcontrib>2. C醫edra (Chair) Coexphal-UAL of Horticulture, Cooperative Studies and Sustainable Development, University of Almer韆, Spain</creatorcontrib><creatorcontrib>1. Department of Informatics, CeiA3, University of Almeria, Almeria, CP 04120, Spain</creatorcontrib><creatorcontrib>4. Department of Electronics and Computer Technology, Facultad de Ciencias, Granada, CP 18071, Spain</creatorcontrib><creatorcontrib>3. Beijing Research Center for Information Technology in Agriculture/National Engineering Research Center for Information Technology in Agriculture/National Engineering Laboratory for Agri-product Quality Traceability/Key Laboratory for Information Technologies in Agriculture, Ministry of Agriculture, Beijing 100097, China</creatorcontrib><title>Image processing methods to evaluate tomato and zucchini damage in post-harvest stages</title><title>International journal of agricultural and biological engineering</title><description>Through the supply chain, the quality or quality change of the products can generate important losses. The quality control in some steps is made manually that supposes a high level of subjectivity, controlling the quality and its evolution using automatic systems can suppose a reduction of the losses. Testing some automatic image analysis techniques in the case of tomatoes and zucchini is the main objective of this study. Two steps in the supply chain are considered, the feeding of the raw products into the handling chain (because low quality generates a reduction of the chain productivity) and the cool storage of the processed products (as the value at the market is reduced). It was proposed to analyze the incoming products at the head the processing line using CCD cameras to detect low quality and/or dirty products (corresponding to specific farmers/suppliers, it should be asked to improve to maintain the productivity of the line). The second stage is analyzing the evolution of the products along the cool chain (storage and transport), the use of an App developed to be use under Android was proposed to substitute the "visual" evaluation used in practice. The algorithms used, including stages of pre-treatment, segmentation, analysis and presentation of the results take account of the short time available and the limited capacity of the batteries. High performance techniques were applied to the homography stage to discard some of the images, resulting in better performance. Also threads and renderscript kernels were created to parallelize the methods used on the resulting images being able to inspect faster the products. The proposed method achieves success rates comparable to, and improving, the expert inspection.</description><subject>Automatic control</subject><subject>Cameras</subject><subject>CCD cameras</subject><subject>Damage assessment</subject><subject>Evolution</subject><subject>Fruits</subject><subject>Image analysis</subject><subject>Image processing</subject><subject>Image segmentation</subject><subject>Inspection</subject><subject>Kernels</subject><subject>Parallel processing</subject><subject>Pretreatment</subject><subject>Productivity</subject><subject>Quality control</subject><subject>Reduction</subject><subject>Smartphones</subject><subject>Storage</subject><subject>Supply chains</subject><subject>Tomatoes</subject><subject>Vision systems</subject><issn>1934-6344</issn><issn>1934-6352</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNo9kF1LwzAUhoMoOKd_QQJetyY5SZNeylA3GHij3oY0SbeWtZ1NOtBfb9zUc3M-OOe8vA9Ct5TkTNBC3Ld505rK54xQSQkRORAlz9CMlsCzAgQ7_685v0RXIbSEFFyBmKH3VWc2Hu_HwfoQmn6DOx-3gws4DtgfzG4y0ae6M6k3vcNfk7Xbpm-wM8fLpsf7IcRsa8aDDxGHmKbhGl3UZhf8zW-eo7enx9fFMlu_PK8WD-vMMgUxA2nKStYAzHlROl-BVJ4xX1SFMxY4CCoNF0UyZGovWakqDiWzwgGlVjmYo7vT32TgY0r6uh2msU-SmpZSUqUgxRwVpy07DiGMvtb7senM-Kkp0UeGutVHhvqPof5hCN_fgmcO</recordid><startdate>20170901</startdate><enddate>20170901</enddate><creator>Alvarez-Bermejo, Jos Antonio</creator><creator>Giagnocavo, Cynthia</creator><creator>Ming, Li</creator><creator>Castillo Morales, Encarnaci髇</creator><creator>P. 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The quality control in some steps is made manually that supposes a high level of subjectivity, controlling the quality and its evolution using automatic systems can suppose a reduction of the losses. Testing some automatic image analysis techniques in the case of tomatoes and zucchini is the main objective of this study. Two steps in the supply chain are considered, the feeding of the raw products into the handling chain (because low quality generates a reduction of the chain productivity) and the cool storage of the processed products (as the value at the market is reduced). It was proposed to analyze the incoming products at the head the processing line using CCD cameras to detect low quality and/or dirty products (corresponding to specific farmers/suppliers, it should be asked to improve to maintain the productivity of the line). The second stage is analyzing the evolution of the products along the cool chain (storage and transport), the use of an App developed to be use under Android was proposed to substitute the "visual" evaluation used in practice. The algorithms used, including stages of pre-treatment, segmentation, analysis and presentation of the results take account of the short time available and the limited capacity of the batteries. High performance techniques were applied to the homography stage to discard some of the images, resulting in better performance. Also threads and renderscript kernels were created to parallelize the methods used on the resulting images being able to inspect faster the products. 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subjects | Automatic control Cameras CCD cameras Damage assessment Evolution Fruits Image analysis Image processing Image segmentation Inspection Kernels Parallel processing Pretreatment Productivity Quality control Reduction Smartphones Storage Supply chains Tomatoes Vision systems |
title | Image processing methods to evaluate tomato and zucchini damage in post-harvest stages |
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