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[[Berkas:AutovisionIIatRDT.jpg|jmpl|Salah satu sistem visipenglihatan mesin yang dikembangkan oleh Omron (dahulu Automatix)]]
Di dalam konteks [[mekatronika]] dan [[Teknik otomasi|otomasi]], '''visipenglihatan mesin''' didefinisikan sebagai bagaimana suatu sistem terotomatisasi (sebagai contoh [[robot]]) dapat melakukan [[inspeksi]] atau pengelihatan otomatis berbasis [[citra]]/ atau gambar yang ditangkap dari alat (umumnya lensa atau kamera) sebagai ''input/'' masukanataumasukan [[sensor]] untuk diolah di dalam [[Unit Pemroses Sentral|prosesor]]/ atau [[komputer]] yang akan menggerakkan [[aktuator]] atau penggerak seperti sistem gerak robot atau [[motor listrik]]. Secara umum, visipenglihatan mesin adalah salah satu contoh pemanfaatan [[kecerdasan buatan]].<ref name=":0">{{Cite web|title=VisiPenglihatan Komputer: Apa itu dan mengapa hal itu penting|url=https://www.sas.com/id_id/insights/analytics/computer-vision.html|website=www.sas.com|language=in|access-date=2022-01-26}}</ref><ref name=":1">{{Cite web|title=Sistem VisiPenglihatan {{!}} KEYENCE Indonesia|url=https://www.keyence.co.id/products/vision/vision-sys/|website=www.keyence.co.id|access-date=2022-01-26}}</ref>
[[Berkas:Machine Vision System.jpg|jmpl|Salah satu penerapan sistem visipenglihatan mesin pada [[Lini perakitan|jalur (line) produksi ban berjalan (conveyor belt)]]]]
SecaraSebagai umumgambaran, visipenglihatan mesin mengandalkan [[Perangkat lunak|piranti lunak]] untuk memroses gambar atau citra di mana salah satu piranti lunak yang umum digunakan di dalam memroses masukan dari visipenglihatan mesin adalah [[MATLAB|Matlab]].<ref name=":0" /><ref name=":1" /> Kemudian, proses dari gambar atau citra tersebut akan digunakan untuk melakukan suatu tindakan atau eksekusi yang dilakukan oleh sebuah [[aktuator]] atau penggerak.
 
Aplikasi dari visipenglihatan mesin ini sangat luas tidak hanya sebagai alat bantu untuk robotika atau sistem mekatronika lainnya tetapi juga dapat digunakan di beberapa bidang seperti [[Kesehatan|kesehatan/medis]], [[pertanian]], [[Makanan|pangan]], [[industri]], [[energi]], [[infrastruktur]], serta [[transportasi]].
 
== Definisi ==
Secara umum, banyak yang menyamakan antara penglihatan mesin dengan [[penglihatan komputer]] (''computer vision''). Perbedaannya adalah, pada penglihatan mesin, ia adalah penerapan dari penglihatan komputer di dunia industri di mana output dari prosesor atau komputer akan diolah menjadi output berupa gerak mekanik atau termal.<ref>{{Cite web|date=2021-05-31|title=Machine Vision vs. Computer Vision—What’s the Difference?|url=https://appen.com/blog/computer-vision-vs-machine-vision/|website=Appen|language=en-GB|access-date=2022-01-30}}</ref>
 
=== Sejarah ===
Awalnya, penerapan dari penglihatan mesin ini digunakan pada salah satu [[supermarket]] di [[New Jersey]] di mana saat itu makanan yang ditawarkan disortir (diseleksi) berdasarkan filter tertentu.<ref>{{Cite web|title=StackPath|url=https://www.vision-systems.com/knowledge-zone/article/14069209/the-history-of-machine-vision|website=www.vision-systems.com|access-date=2022-01-30}}</ref>
 
== Metode ==
[[Berkas:Matplotlib3 histogram.svg|jmpl|Histogram adalah salah satu metode umum di dalam statistik yang digunakan dalam analisis citra sebagai salah satu penunjang sistem visipenglihatan mesin]]
Secara umum, visipenglihatan mesin adalah penerapan lebih lanjut dari kecerdasan buatan yang menggunakan prinsip-prinsip [[matematika]] seperti [[statistik]] ([[histogram]], [[distribusi normal]], [[Simpangan baku|standar deviasi]]), [[Matriks (matematika)|matriks]], Jaringan Bayesian, [[Algoritma genetik|Algoritma Genetik]], [[Pengambangan (pengolahan citra)|pengambangan (thresholding)]], [[Logika kabur|logika fuzzy/ atau kabur]], [[Vektor satuan|vektor]] (terutama ''[[Support-vector machine|support vector machines]]''), dan [[Analisis numerik|komputasi/ atau metode numerik]] serta fisika terutama [[sensor]] dan [[Optika|prinsip alat-alat optik]] serta kekuatan [[Memori (komputer)|memori dari komputer]] (terkait [[Memori akses acak|RAM]]).<ref name=":2">{{Cite journal|last=Wildes|first=Richard P.|last2=Asmuth|first2=Jane C.|last3=Green|first3=Gilbert L.|last4=Hsu|first4=Steven C.|last5=Kolczynski|first5=Raymond J.|last6=Matey|first6=James R.|last7=McBride|first7=Sterling E.|date=1996-01|title=A machine-vision system for iris recognition|url=http://link.springer.com/10.1007/BF01246633|journal=Machine Vision and Applications|language=en|volume=9|issue=1|pages=1–8|doi=10.1007/BF01246633|issn=0932-8092}}</ref>
[[Berkas:PLC Block Diagram.jpg|jmpl|Contoh blok diagram dari PLC (''[[Kontrol logika terprogram|Programmable Logic Controller]]'') yang juga memiliki prinsip yang sama dengan visipenglihatan mesin.]]
Secara umum, kerja dari sistem visipenglihatan mesin menyerupai kerja dari blok diagram [[Sistem kendali|kendali]] secara umum di mana terdapat masukan/ atau ''input'', pengolahan data, serta ''output/'' atau keluaran.
 
=== Input/Masukan ===
Masukan atau input yang akan diolah oleh sistem sendiri ditangkap oleh alat berupa [[sensor]] atau [[kamera]] yang akan menangkap citra atau gambar dari objek yang akan diolah oleh aktuator.
 
Umumnya, kamera yang digunakan adalah kamera yang memiliki spesifikasi [[piksel]] yang tinggi serta mampu untuk menangkap gambar atau video dalam [[Tingkat bingkai|laju frame per detik (''frame per second'')]] yang bagus seperti [[kamera berkecepatan tinggi]] (''high speed camera''). Hal ini bertujuan untuk mendapatkan hasil citra atau gambar yang bagus dan tidak terdapat blur atau gambar yang kabur. Untuk piranti[[perangkat keras/]] (''hardware'') lainnya adalah sumber cahaya.<ref>{{Cite web|title=Designing a machine-vision system|url=https://spie.org/news/designing-a-machine-vision-system|website=spie.org|access-date=2022-01-29}}</ref>
 
=== Pengolahan Data ===
Di sini, data yang ditangkap oleh sensor (terutama citra), akan diolah secara matematik oleh piranti lunak. Pada bagian inilah kerja dari statistik, matriks, jaringan Bayesian, [[Logika kabur|logika fuzzy/ atau kabur]], serta algoritma genetik mulai digunakan. Sementara, untuk matriks, secara umum sistem visipenglihatan mesin menggunakan metode seperti sobel dan Fre-Chen sebagai alat bantu analisis segmentasi dan deskripsi dari piksel.<ref name=":3">{{Cite journal|last=Kurada|first=S.|last2=Bradley|first2=C.|date=1997-04|title=A machine vision system for tool wear assessment|url=https://linkinghub.elsevier.com/retrieve/pii/S0301679X96000588|journal=Tribology International|language=en|volume=30|issue=4|pages=295–304|doi=10.1016/S0301-679X(96)00058-8}}</ref><ref name=":4">{{Cite journal|last=Ureña|first=R|last2=Rodrı́guez|first2=F|last3=Berenguel|first3=M|date=2001-07|title=A machine vision system for seeds quality evaluation using fuzzy logic|url=https://linkinghub.elsevier.com/retrieve/pii/S0168169901001508|journal=Computers and Electronics in Agriculture|language=en|volume=32|issue=1|pages=1–20|doi=10.1016/S0168-1699(01)00150-8}}</ref> Selain itu, prinsip dari eigenvektor dan eigenvalue sendiri juga digunakan untuk [[analisis data]]. Serta, untuk pengolahan citra atau gambar digunakan metode-metode [[Pengambangan (pengolahan citra)|pengambangan (thresholding)]]. Pada bagian pengambangan ini, prinsip-prinsip statistik seperti [[histogram]], [[distribusi normal]], [[Simpangan baku|standar deviasi]] serta [[Matriks (matematika)|matriks]] digunakan di dalam analisis piksel sebagai salah satu metode dari interpretasi citra.<ref name=":4"/><ref name=":5">{{Cite journal|last=Patel|first=Krishna Kumar|last2=Kar|first2=A.|last3=Jha|first3=S. N.|last4=Khan|first4=M. A.|date=2012-04|title=Machine vision system: a tool for quality inspection of food and agricultural products|url=http://link.springer.com/10.1007/s13197-011-0321-4|journal=Journal of Food Science and Technology|language=en|volume=49|issue=2|pages=123–141|doi=10.1007/s13197-011-0321-4|issn=0022-1155|pmc=PMC3550871|pmid=23572836}}</ref><ref name=":4">{{Cite journal|last=Ureña|first=R|last2=Rodrı́guez|first2=F|last3=Berenguel|first3=M|date=2001-07|title=A machine vision system for seeds quality evaluation using fuzzy logic|url=https://linkinghub.elsevier.com/retrieve/pii/S0168169901001508|journal=Computers and Electronics in Agriculture|language=en|volume=32|issue=1|pages=1–20|doi=10.1016/S0168-1699(01)00150-8}}</ref>
 
[[Histogram]] sendiri digunakan di dalam analisis piksel dari citra atau gambar yang digunakan sebagai masukan/input dari sistem yang akan diolah pirantiperangkat lunak.
[[Berkas:African Cape Daisy (tresholded).svg|jmpl|Salah satu contoh hasil pengambangan pada bunga daisy (African Cape). Sistem visipenglihatan mesin banyak menggunakan metode ini sebagai salah satu metode di dalam komputasinya. ]]
Untuk prosesor atau komputer yang digunakan, pada era modern saat ini sudah banyak komputer dengan spesifikasi RAM dan memori yang cukup untuk melakukan prinsip [[Pengambangan (pengolahan citra)|pengambangan (thresholding)]] terutama komputer dengan [[Unit Pemroses Sentral|prosesor]] terkini yang lebih cepat dalam frekuensi serta jumlah memori yang besar dengan ukuran yang kecil.
 
=== Output/ atau Keluaran ===
Output yang dihasilkan dari sistem pengolahan data (pada umumnya RAM) bisa berupa citra atau output mekanik seperti pergerakan dan [[Panas|panas/ atau kalor]] apabila [[aktuator]] atau penggarak tersebut digunakan di dalam sistem energi seperti di [[sistem pendinginan]] dan tata udara atau di [[Pembangkit listrik|pembangkit energi]].
 
== Aplikasi ==
Secara umum, sistem visipenglihatan mesin tidak hanya digunakan di dalam industri tetapi juga digunakan di sistem lain seperti transportasi, pertanian, dan kesehatan.
[[Berkas:Eye iris.jpg|jmpl|Iris atau retina pelangi. Deteksi visipenglihatan mesin dapat digunakan untuk mengklasifikasi permukaan iris yang berbeda pada setiap orang.]]
 
=== Aplikasi di Bidang Kesehatan ===
 
* Deteksi [[Selaput pelangi|iris mata]]<ref name=":2" />
* Pengenalan [[wajah]].<ref>{{Cite journal|last=Jalled|first=Fares|date=2017-05-08|title=Face Recognition Machine Vision System Using Eigenfaces|url=http://arxiv.org/abs/1705.02782|journal=arXiv:1705.02782 [cs]}}</ref>
* Robot untuk operasi.<ref>{{Cite web|title=Robot performs first laparoscopic surgery without human help|url=https://www.sciencedaily.com/releases/2022/01/220126143954.htm|website=ScienceDaily|language=en|access-date=2022-01-29}}</ref><ref>{{Cite web|title=Robot performs 1st laparoscopic surgery without human help|url=https://www.eurekalert.org/news-releases/941011|website=EurekAlert!|language=en|access-date=2022-01-29}}</ref>
 
=== Aplikasi di Bidang Pertanian ===
Penyeleksian tingkat kematangan [[buah]]<ref>{{Cite journal|last=Blasco|first=J|last2=Aleixos|first2=N|last3=Moltó|first3=E|date=2003-08|title=Machine Vision System for Automatic Quality Grading of Fruit|url=https://linkinghub.elsevier.com/retrieve/pii/S1537511003000886|journal=Biosystems Engineering|language=en|volume=85|issue=4|pages=415–423|doi=10.1016/S1537-5110(03)00088-6}}</ref><ref name=":5" />▼
 
* Penyeleksian tingkat kematangan [[buah]]<ref name=":5" /><ref>{{Cite journal|last=Blasco|first=J|last2=Aleixos|first2=N|last3=Moltó|first3=E|date=2003-08|title=Machine Vision System for Automatic Quality Grading of Fruit|url=https://linkinghub.elsevier.com/retrieve/pii/S1537511003000886|journal=Biosystems Engineering|language=en|volume=85|issue=4|pages=415–423|doi=10.1016/S1537-5110(03)00088-6}}</ref>
* Robot pemetik buah.<ref>{{Cite journal|last=Bulanon|first=D.M.|last2=Kataoka|first2=T.|last3=Okamoto|first3=H.|last4=Hata|first4=S.|date=2004-08|title=Development of a real-time machine vision system for the apple harvesting robot|url=https://ieeexplore.ieee.org/document/1491474|journal=SICE 2004 Annual Conference|volume=1|pages=595–598 vol. 1}}</ref><ref>{{Cite journal|last=Baigvand|first=Mehrdad|last2=Banakar|first2=Ahmad|last3=Minaei|first3=Saeed|last4=Khodaei|first4=Jalal|last5=Behroozi-Khazaei|first5=Nasser|date=2015-11|title=Machine vision system for grading of dried figs|url=https://linkinghub.elsevier.com/retrieve/pii/S0168169915003324|journal=Computers and Electronics in Agriculture|language=en|volume=119|pages=158–165|doi=10.1016/j.compag.2015.10.019}}</ref>
* Inspeksi ukuran biji/ atau [[Bulir (botani)|bulir]].<ref name=":4" /><ref>{{Cite journal|last=Vithu|first=P.|last2=Moses|first2=J.A.|date=2016-10|title=Machine vision system for food grain quality evaluation: A review|url=https://linkinghub.elsevier.com/retrieve/pii/S092422441630084X|journal=Trends in Food Science & Technology|language=en|volume=56|pages=13–20|doi=10.1016/j.tifs.2016.07.011}}</ref><ref name=":4" /><ref>{{Cite journal|last=Luo|first=X|last2=Jayas|first2=Ds|last3=Symons|first3=Sj|date=1999-07|title=Identification of Damaged Kernels in Wheat using a Colour Machine Vision System|url=https://linkinghub.elsevier.com/retrieve/pii/S0733521098902405|journal=Journal of Cereal Science|language=en|volume=30|issue=1|pages=49–59|doi=10.1006/jcrs.1998.0240}}</ref><ref>{{Cite journal|last=Branson|first=Steve|last2=Van Horn|first2=Grant|last3=Wah|first3=Catherine|last4=Perona|first4=Pietro|last5=Belongie|first5=Serge|date=2014-02-20|title=The Ignorant Led by the Blind: A Hybrid Human–Machine Vision System for Fine-Grained Categorization|url=http://link.springer.com/10.1007/s11263-014-0698-4|journal=International Journal of Computer Vision|language=en|doi=10.1007/s11263-014-0698-4|issn=0920-5691}}</ref><ref>{{Cite journal|last=Belan|first=Peterson Adriano|last2=de Macedo|first2=Robson Aparecido Gomes|last3=Alves|first3=Wonder Alexandre Luz|last4=Santana|first4=José Carlos Curvelo|last5=Araújo|first5=Sidnei Alves|date=2020-12|title=Machine vision system for quality inspection of beans|url=http://link.springer.com/10.1007/s00170-020-06226-5|journal=The International Journal of Advanced Manufacturing Technology|language=en|volume=111|issue=11-12|pages=3421–3435|doi=10.1007/s00170-020-06226-5|issn=0268-3768}}</ref>▼
▲Penyeleksian* tingkatInspeksi kematanganukuran [[buahumbi]].<ref>{{Cite journal|last=BlascoElMasry|first=JGamal|last2=AleixosCubero|first2=NSergio|last3=Moltó|first3=EEnrique|last4=Blasco|first4=José|date=20032012-0809|title=MachineIn-line Visionsorting Systemof forirregular Automaticpotatoes Qualityby Gradingusing ofautomated computer-based machine vision Fruitsystem|url=https://linkinghub.elsevier.com/retrieve/pii/S1537511003000886S0260877412001690|journal=BiosystemsJournal of Food Engineering|language=en|volume=85112|issue=41-2|pages=415–42360–68|doi=10.1016/S1537-5110(j.jfoodeng.2012.03)00088-6.027}}</ref><ref name=":5" />
* Inspeksi ukuran [[jamur]].<ref>{{Cite journal|last=P. H. Heinemann|last2=R. Hughes|last3=C. T. Morrow|last4=H. J. Sommer|last5=Iii|last6=R. B. Beelman|last7=P. J. Wuest|date=1994|title=Grading of Mushrooms Using a Machine Vision System|url=http://elibrary.asabe.org/abstract.asp??JID=3&AID=28255&CID=t1994&v=37&i=5&T=1|journal=Transactions of the ASAE|language=en|volume=37|issue=5|pages=1671–1677|doi=10.13031/2013.28255|issn=2151-0059}}</ref>▼
 
=== Aplikasi di Bidang Perikanan ===
▲Inspeksi ukuran biji/[[Bulir (botani)|bulir]].<ref>{{Cite journal|last=Vithu|first=P.|last2=Moses|first2=J.A.|date=2016-10|title=Machine vision system for food grain quality evaluation: A review|url=https://linkinghub.elsevier.com/retrieve/pii/S092422441630084X|journal=Trends in Food Science & Technology|language=en|volume=56|pages=13–20|doi=10.1016/j.tifs.2016.07.011}}</ref><ref name=":4" /><ref>{{Cite journal|last=Luo|first=X|last2=Jayas|first2=Ds|last3=Symons|first3=Sj|date=1999-07|title=Identification of Damaged Kernels in Wheat using a Colour Machine Vision System|url=https://linkinghub.elsevier.com/retrieve/pii/S0733521098902405|journal=Journal of Cereal Science|language=en|volume=30|issue=1|pages=49–59|doi=10.1006/jcrs.1998.0240}}</ref><ref>{{Cite journal|last=Branson|first=Steve|last2=Van Horn|first2=Grant|last3=Wah|first3=Catherine|last4=Perona|first4=Pietro|last5=Belongie|first5=Serge|date=2014-02-20|title=The Ignorant Led by the Blind: A Hybrid Human–Machine Vision System for Fine-Grained Categorization|url=http://link.springer.com/10.1007/s11263-014-0698-4|journal=International Journal of Computer Vision|language=en|doi=10.1007/s11263-014-0698-4|issn=0920-5691}}</ref><ref>{{Cite journal|last=Belan|first=Peterson Adriano|last2=de Macedo|first2=Robson Aparecido Gomes|last3=Alves|first3=Wonder Alexandre Luz|last4=Santana|first4=José Carlos Curvelo|last5=Araújo|first5=Sidnei Alves|date=2020-12|title=Machine vision system for quality inspection of beans|url=http://link.springer.com/10.1007/s00170-020-06226-5|journal=The International Journal of Advanced Manufacturing Technology|language=en|volume=111|issue=11-12|pages=3421–3435|doi=10.1007/s00170-020-06226-5|issn=0268-3768}}</ref>
 
* Inspeksi ukuranbudidaya [[umbi]].perikanan (''aquaculture'')<ref>{{Cite journal|last=ElMasrySaberioon|first=GamalMohammadmehdi|last2=CuberoGholizadeh|first2=SergioAsa|last3=MoltóCisar|first3=EnriquePetr|last4=BlascoPautsina|first4=JoséAliaksandr|last5=Urban|first5=Jan|date=2012-092017|title=In-line sortingApplication of irregularmachine potatoesvision bysystems usingin automatedaquaculture computerwith emphasis on fish: state-basedof-the-art machineand visionkey systemissues|url=https://linkinghubonlinelibrary.elsevierwiley.com/retrievedoi/piiabs/S026087741200169010.1111/raq.12143|journal=JournalReviews ofin Food EngineeringAquaculture|language=en|volume=1129|issue=1-24|pages=60–68369–387|doi=10.10161111/jraq.jfoodeng.2012.03.02712143|issn=1753-5131}}</ref>
 
▲Inspeksi ukuran [[jamur]].<ref>{{Cite journal|last=P. H. Heinemann|last2=R. Hughes|last3=C. T. Morrow|last4=H. J. Sommer|last5=Iii|last6=R. B. Beelman|last7=P. J. Wuest|date=1994|title=Grading of Mushrooms Using a Machine Vision System|url=http://elibrary.asabe.org/abstract.asp??JID=3&AID=28255&CID=t1994&v=37&i=5&T=1|journal=Transactions of the ASAE|language=en|volume=37|issue=5|pages=1671–1677|doi=10.13031/2013.28255|issn=2151-0059}}</ref>
 
=== Aplikasi di Bidang Pangan ===
 
* Inspeksi kematangan hasil [[roti]].<ref>{{Cite journal|last=Abdullah|first=Mohd Zaid|last2=Aziz|first2=Sabina Abdul|last3=Mohamed|first3=Abdul Manan|date=2000-03|title=QUALITY INSPECTION OF BAKERY PRODUCTS USING A COLOR-BASED MACHINE VISION SYSTEM|url=https://onlinelibrary.wiley.com/doi/10.1111/j.1745-4557.2000.tb00194.x|journal=Journal of Food Quality|language=en|volume=23|issue=1|pages=39–50|doi=10.1111/j.1745-4557.2000.tb00194.x|issn=0146-9428}}</ref>
 
=== Aplikasi di Bidang Industri ===
[[Robotika|Robotika Industri]].<ref>{{Cite journal|last=Golnabi|first=H.|last2=Asadpour|first2=A.|date=2007-12|title=Design and application of industrial machine vision systems|url=https://linkinghub.elsevier.com/retrieve/pii/S0736584507000233|journal=Robotics and Computer-Integrated Manufacturing|language=en|volume=23|issue=6|pages=630–637|doi=10.1016/j.rcim.2007.02.005}}</ref>
 
[[Gaya gesek|Keausan peralatan manufaktur]] serta kekasaran permukaan.<ref name=":3" /><ref>{{Cite journal|last=Luk|first=F|last2=Huynh|first2=V|last3=North|first3=W|date=1989-12|title=Measurement of surface roughness by a machine vision system|url=https://iopscience.iop.org/article/10.1088/0022-3735/22/12/001|journal=Journal of Physics E: Scientific Instruments|volume=22|issue=12|pages=977–980|doi=10.1088/0022-3735/22/12/001|issn=0022-3735}}</ref>▼
 
Inspeksi [[Peralatan elektronik|produk elektrik]].<ref>{{Cite journal|last=Lahajnar|first=Franci|last2=Bernard|first2=Rok|last3=Pernuš|first3=Franjo|last4=Kovačič|first4=Stanislav|date=2002-01|title=Machine vision system for inspecting electric plates|url=https://linkinghub.elsevier.com/retrieve/pii/S0166361501001348|journal=Computers in Industry|language=en|volume=47|issue=1|pages=113–122|doi=10.1016/S0166-3615(01)00134-8}}</ref><ref>{{Cite journal|last=Furferi|first=Rocco|last2=Governi|first2=Lapo|last3=Puggelli|first3=Luca|last4=Servi|first4=Michaela|last5=Volpe|first5=Yary|date=2019-06-13|title=Machine Vision System for Counting Small Metal Parts in Electro-Deposition Industry|url=https://www.mdpi.com/2076-3417/9/12/2418|journal=Applied Sciences|language=en|volume=9|issue=12|pages=2418|doi=10.3390/app9122418|issn=2076-3417}}</ref>▼
 
Inspeksi hasil produksi.<ref>{{Cite journal|last=Kazanskiy|first=N. L.|last2=Popov|first2=S. B.|date=2010-03|title=Machine vision system for singularity detection in monitoring the long process|url=http://link.springer.com/10.3103/S1060992X10010042|journal=Optical Memory and Neural Networks|language=en|volume=19|issue=1|pages=23–30|doi=10.3103/S1060992X10010042|issn=1060-992X}}</ref><ref>{{Cite journal|last=Wu|first=Yu|last2=Lu|first2=Yanjie|date=2019-09|title=An intelligent machine vision system for detecting surface defects on packing boxes based on support vector machine|url=http://journals.sagepub.com/doi/10.1177/0020294019858175|journal=Measurement and Control|language=en|volume=52|issue=7-8|pages=1102–1110|doi=10.1177/0020294019858175|issn=0020-2940}}</ref>▼
 
Inspeksi ''packing''/kemasan.<ref>{{Cite journal|last=Lenty|first=Bartosz|date=2019-11-06|editor-last=Romaniuk|editor-first=Ryszard S.|editor2-last=Linczuk|editor2-first=Maciej|title=Machine vision system for quality control of molded plastic packaging|url=https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11176/2536697/Machine-vision-system-for-quality-control-of-molded-plastic-packaging/10.1117/12.2536697.full|journal=Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019|location=Wilga, Poland|publisher=SPIE|pages=77|doi=10.1117/12.2536697|isbn=978-1-5106-3065-9}}</ref>▼
 
Inspeksi produk [[tekstil]].<ref>{{Cite journal|last=Çelik|first=H.İ.|last2=Dülger|first2=L.C.|last3=Topalbekiroğlu|first3=M.|date=2014-06-03|title=Development of a machine vision system: real-time fabric defect detection and classification with neural networks|url=http://www.tandfonline.com/doi/abs/10.1080/00405000.2013.827393|journal=The Journal of The Textile Institute|language=en|volume=105|issue=6|pages=575–585|doi=10.1080/00405000.2013.827393|issn=0040-5000}}</ref>▼
 
Alat bantu di dalam* [[LasRobotika|pengelasanRobotika Industri]].<ref>{{Cite journal|last=HuangGolnabi|first=WeiH.|last2=KovacevicAsadpour|first2=RadovanA.|date=20122007-1112|title=DevelopmentDesign ofand aapplication real-timeof laser-basedindustrial machine vision system to monitor and control welding processessystems|url=httphttps://linklinkinghub.springerelsevier.com/10.1007retrieve/pii/s00170-012-3902-0S0736584507000233|journal=TheRobotics Internationaland Journal of AdvancedComputer-Integrated Manufacturing Technology|language=en|volume=6323|issue=1-46|pages=235–248630–637|doi=10.10071016/s00170-012-3902-0|issn=0268-3768}}</ref><ref>{{Citation|title=Profil Dosen DTM - Drj. Ario Sunar Baskoro, Srcim.T2007. , M02.T. , M.Eng|url=https://www.youtube.com/watch?v=MffNGmD9D24|accessdate=2022-01-29|language=id-ID005}}</ref>
▲* [[Gaya gesek|Keausan peralatan manufaktur]] serta kekasaran permukaan.<ref name=":3" /><ref>{{Cite journal|last=Luk|first=F|last2=Huynh|first2=V|last3=North|first3=W|date=1989-12|title=Measurement of surface roughness by a machine vision system|url=https://iopscience.iop.org/article/10.1088/0022-3735/22/12/001|journal=Journal of Physics E: Scientific Instruments|volume=22|issue=12|pages=977–980|doi=10.1088/0022-3735/22/12/001|issn=0022-3735}}</ref>
▲* Inspeksi [[Peralatan elektronik|produk elektrik]].<ref>{{Cite journal|last=Lahajnar|first=Franci|last2=Bernard|first2=Rok|last3=Pernuš|first3=Franjo|last4=Kovačič|first4=Stanislav|date=2002-01|title=Machine vision system for inspecting electric plates|url=https://linkinghub.elsevier.com/retrieve/pii/S0166361501001348|journal=Computers in Industry|language=en|volume=47|issue=1|pages=113–122|doi=10.1016/S0166-3615(01)00134-8}}</ref><ref>{{Cite journal|last=Furferi|first=Rocco|last2=Governi|first2=Lapo|last3=Puggelli|first3=Luca|last4=Servi|first4=Michaela|last5=Volpe|first5=Yary|date=2019-06-13|title=Machine Vision System for Counting Small Metal Parts in Electro-Deposition Industry|url=https://www.mdpi.com/2076-3417/9/12/2418|journal=Applied Sciences|language=en|volume=9|issue=12|pages=2418|doi=10.3390/app9122418|issn=2076-3417}}</ref>
▲* Inspeksi hasil produksi.<ref>{{Cite journal|last=Kazanskiy|first=N. L.|last2=Popov|first2=S. B.|date=2010-03|title=Machine vision system for singularity detection in monitoring the long process|url=http://link.springer.com/10.3103/S1060992X10010042|journal=Optical Memory and Neural Networks|language=en|volume=19|issue=1|pages=23–30|doi=10.3103/S1060992X10010042|issn=1060-992X}}</ref><ref>{{Cite journal|last=Wu|first=Yu|last2=Lu|first2=Yanjie|date=2019-09|title=An intelligent machine vision system for detecting surface defects on packing boxes based on support vector machine|url=http://journals.sagepub.com/doi/10.1177/0020294019858175|journal=Measurement and Control|language=en|volume=52|issue=7-8|pages=1102–1110|doi=10.1177/0020294019858175|issn=0020-2940}}</ref>
▲* Inspeksi ''packing''/ atau kemasan.<ref>{{Cite journal|last=Lenty|first=Bartosz|date=2019-11-06|editor-last=Romaniuk|editor-first=Ryszard S.|editor2-last=Linczuk|editor2-first=Maciej|title=Machine vision system for quality control of molded plastic packaging|url=https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11176/2536697/Machine-vision-system-for-quality-control-of-molded-plastic-packaging/10.1117/12.2536697.full|journal=Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019|location=Wilga, Poland|publisher=SPIE|pages=77|doi=10.1117/12.2536697|isbn=978-1-5106-3065-9}}</ref>
▲* Inspeksi produk [[tekstil]].<ref>{{Cite journal|last=Çelik|first=H.İ.|last2=Dülger|first2=L.C.|last3=Topalbekiroğlu|first3=M.|date=2014-06-03|title=Development of a machine vision system: real-time fabric defect detection and classification with neural networks|url=http://www.tandfonline.com/doi/abs/10.1080/00405000.2013.827393|journal=The Journal of The Textile Institute|language=en|volume=105|issue=6|pages=575–585|doi=10.1080/00405000.2013.827393|issn=0040-5000}}</ref>
* Alat bantu di dalam [[Las|pengelasan]].<ref>{{Cite journal|last=Huang|first=Wei|last2=Kovacevic|first2=Radovan|date=2012-11|title=Development of a real-time laser-based machine vision system to monitor and control welding processes|url=http://link.springer.com/10.1007/s00170-012-3902-0|journal=The International Journal of Advanced Manufacturing Technology|language=en|volume=63|issue=1-4|pages=235–248|doi=10.1007/s00170-012-3902-0|issn=0268-3768}}</ref><ref>{{Citation|title=Profil Dosen DTM - Dr. Ario Sunar Baskoro, S.T. , M.T. , M.Eng|url=https://www.youtube.com/watch?v=MffNGmD9D24|accessdate=2022-01-29|language=id-ID}}</ref>
* Inspeksi bagian-bagian mekanik atau suku cadang.<ref>{{Cite journal|last=Jain|first=Tushar|last2=Gupta|first2=Meenu|last3=Sardana|first3=H.K.|date=2018-10-08|title=Unmanned machine vision system for automated recognition of mechanical parts|url=https://www.emerald.com/insight/content/doi/10.1108/IJIUS-03-2018-0008/full/html|journal=International Journal of Intelligent Unmanned Systems|language=en|volume=6|issue=4|pages=184–196|doi=10.1108/IJIUS-03-2018-0008|issn=2049-6427}}</ref>
 
=== Aplikasi di Bidang Energi ===
Analisis aliran [[fluida]]<ref>{{Cite journal|last=Valenzuela-Delgado|first=Monica|last2=Flores-Fuentes|first2=Wendy|last3=Bravo-Zanoguera|first3=Miguel E.|last4=Ortiz-Perez|first4=Alejandro S.|last5=Hernandez-Balbuena|first5=Daniel|last6=Rivas-Lopez|first6=Moises|last7=Sergiyenko|first7=Oleg|last8=Gonzalez-Navarro|first8=Felix F.|date=2017-06|title=Machine vision system to measuring the velocity field in a fluid by Particle Image Velocimetry: Special Case of Magnetohydrodynamics|url=https://ieeexplore.ieee.org/document/8001489/|journal=2017 IEEE 26th International Symposium on Industrial Electronics (ISIE)|location=Edinburgh|publisher=IEEE|pages=1621–1625|doi=10.1109/ISIE.2017.8001489|isbn=978-1-5090-1412-5}}</ref>▼
 
▲* Analisis aliran [[fluida]]<ref>{{Cite journal|last=Valenzuela-Delgado|first=Monica|last2=Flores-Fuentes|first2=Wendy|last3=Bravo-Zanoguera|first3=Miguel E.|last4=Ortiz-Perez|first4=Alejandro S.|last5=Hernandez-Balbuena|first5=Daniel|last6=Rivas-Lopez|first6=Moises|last7=Sergiyenko|first7=Oleg|last8=Gonzalez-Navarro|first8=Felix F.|date=2017-06|title=Machine vision system to measuring the velocity field in a fluid by Particle Image Velocimetry: Special Case of Magnetohydrodynamics|url=https://ieeexplore.ieee.org/document/8001489/|journal=2017 IEEE 26th International Symposium on Industrial Electronics (ISIE)|location=Edinburgh|publisher=IEEE|pages=1621–1625|doi=10.1109/ISIE.2017.8001489|isbn=978-1-5090-1412-5}}</ref>
* Robot pendeteksi kebocoran gas mudah terbakar (''flammable gas'').<ref>{{Cite journal|last=Rahardi|first=Gamma Aditya|last2=Anam|first2=Khairul|last3=Chaidir|first3=Ali Rizal|last4=Larasati|first4=Devita Ayu|date=2021-09-29|title=Navigation System for Olfactory Mobile Robot by Using Machine Vision System|url=http://repository.unej.ac.id/xmlui/handle/123456789/105526|language=en}}</ref>
 
=== Aplikasi di Bidang Transportasi ===
Pendeteksi jalur kedatangan.<ref>{{Cite journal|last=Lee|first=Joon Woong|date=2002-04|title=A Machine Vision System for Lane-Departure Detection|url=https://linkinghub.elsevier.com/retrieve/pii/S1077314202909586|journal=Computer Vision and Image Understanding|language=en|volume=86|issue=1|pages=52–78|doi=10.1006/cviu.2002.0958}}</ref>
 
Alat* bantuPendeteksi [[kendaraan]]jalur kedatangan.<ref>{{Cite journal|last=TsugawaLee|first=S.Joon Woong|date=Aug./19942002-04|title=Vision-basedA vehiclesMachine inVision Japan:System machinefor vision systems and driving controlLane-Departure systemsDetection|url=httphttps://ieeexplorelinkinghub.ieeeelsevier.orgcom/documentretrieve/303790pii/S1077314202909586|journal=IEEEComputer TransactionsVision onand IndustrialImage ElectronicsUnderstanding|language=en|volume=4186|issue=41|pages=398–40552–78|doi=10.11091006/41cviu.2002.3037900958}}</ref>
* Alat bantu [[kendaraan]].<ref>{{Cite journal|last=Tsugawa|first=S.|date=Aug./1994|title=Vision-based vehicles in Japan: machine vision systems and driving control systems|url=http://ieeexplore.ieee.org/document/303790/|journal=IEEE Transactions on Industrial Electronics|volume=41|issue=4|pages=398–405|doi=10.1109/41.303790}}</ref>
 
* Inspeksi [[kereta api]].<ref>{{Cite web|title=A Machine Vision System for Monitoring Railcar Health: Preliminary Results, TD-04-008 - RailTEC|url=https://railtec.illinois.edu/report/a-machine-vision-system-for-monitoring-railcar-health-preliminary-results-td-04-008/|language=en-US|access-date=2022-01-29}}</ref>
* Inspeksi [[Rel|rel kereta api]].<ref>{{Cite journal|last=Min|first=Yongzhi|last2=Xiao|first2=Benyu|last3=Dang|first3=Jianwu|last4=Yue|first4=Biao|last5=Cheng|first5=Tiandong|date=2018-12|title=Real time detection system for rail surface defects based on machine vision|url=https://jivp-eurasipjournals.springeropen.com/articles/10.1186/s13640-017-0241-y|journal=EURASIP Journal on Image and Video Processing|language=en|volume=2018|issue=1|pages=3|doi=10.1186/s13640-017-0241-y|issn=1687-5281}}</ref>
 
=== Aplikasi di Bidang Infrastruktur ===
 
* Inspeksi [[jembatan]].<ref>{{Cite journal|last=Lee|first=Jeong Ho|last2=Lee|first2=Jong Min|last3=Kim|first3=Hyung Jin|last4=Moon|first4=Young Shik|date=2008-05|title=Machine Vision System for Automatic Inspection of Bridges|url=https://ieeexplore.ieee.org/document/4566507/|journal=2008 Congress on Image and Signal Processing|volume=3|pages=363–366|doi=10.1109/CISP.2008.672}}</ref>
 
== Bahan Bacaan ==
Beberapa bahan bacaan yang dapat dirujuk terkait sistem visipenglihatan mesin:
 
* ''Three-Dimensional Machine Vision'' (Kanade, 1987)<ref>{{Cite book|last=Kanade|first=Takeo|date=1987|url=https://www.worldcat.org/oclc/852791356|title=Three-Dimensional Machine Vision|location=Boston, MA|publisher=Springer US|isbn=978-1-4613-1981-8|oclc=852791356}}</ref>
* ''Development of a Machine Vision System for Automated Structural Assembly'' (Sydow, 1992)<ref>{{Cite book|last=Sydow|first=P. Daniel|date=1992|url=https://books.google.co.id/books?id=7304AQAAIAAJ&dq=Machine+Vision+System&hl=id&source=gbs_navlinks_s|title=Development of a Machine Vision System for Automated Structural Assembly|publisher=National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program|language=en}}</ref>
* ''Machine Vision'' (Jain, 1995) <ref>{{Cite book|last=Jain|first=Ramesh|date=1995|url=https://www.worldcat.org/oclc/31933939|title=Machine vision|location=New York|publisher=McGraw-Hill|isbn=0-07-032018-7|others=Rangachar Kasturi, Brian G. Schunck|oclc=31933939}}</ref>
* ''Understanding and Applying Machine Vision, Second Edition, Revised and Expanded'' (Zeuch, 2000)<ref>{{Cite book|last=Zuech|first=Nello|date=2000|url=https://www.worldcat.org/oclc/47009593|title=Understanding and applying machine vision|location=New York|publisher=Marcel Dekker|isbn=0-585-36290-4|edition=2nd ed., rev. and expanded|others=Nello Zuech|oclc=47009593}}</ref>
* ''Machine Vision for the Inspection of Natural Products'' (Graves and Batchelor, 2003)<ref>{{Cite book|date=2003|url=https://www.worldcat.org/oclc/56116331|title=Machine vision for the inspection of natural products|location=London|publisher=Springer|isbn=1-85233-853-9|others=Mark Graves, Bruce G. Batchelor|oclc=56116331}}</ref>
* ''Machine Vision Volume 1'' (Snyder, 2004)<ref>{{Cite book|last=Snyder|first=Wesley E.|date=2004|url=https://www.worldcat.org/oclc/52216294|title=Machine vision|location=Cambridge, UK|publisher=Cambridge University Press|isbn=0-521-83046-X|others=Hairong Qi|oclc=52216294}}</ref>
* ''Machine Vision: Theory, Algorithms, Practicalities'' (Davies, 2005)<ref>{{Cite book|last=Davies|first=E. R.|date=2005|url=https://www.worldcat.org/oclc/162571652|title=Machine vision : theory, algorithms, practicalities|location=Amsterdam|publisher=Elsevier|isbn=978-0-08-047324-6|edition=3rd ed|oclc=162571652}}</ref>
* ''Handbook of Machine Vision'' (Hornberg, 2006)<ref>{{Cite book|date=2006|url=https://www.worldcat.org/oclc/64967366|title=Handbook of machine vision|location=Weinheim|publisher=Wiley-VCH|isbn=3-527-40584-4|others=Alexander Hornberg|oclc=64967366}}</ref>
* ''Issues on Machine Vision'' (Pieroni, 2014)<ref>{{Cite book|date=1989|url=https://www.worldcat.org/oclc/556638516|title=Issues on machine vision|location=Wien|publisher=Springer-Verlag|isbn=978-3-7091-2830-5|others=Goffredo G. Pieroni, International Centre for Mechanical Sciences|oclc=556638516}}</ref>
* ''Handbook of 3D Machine Vision: Optical Metrology and Imaging'' (Zhang, 2016)<ref>{{Cite book|date=2013|url=https://www.worldcat.org/oclc/834627776|title=Handbook of 3D machine vision : optical metrology and imaging|location=Boca Raton|publisher=CRC Press, Taylor & Francis Group|isbn=978-1-4398-7220-8|others=Zhang Song|oclc=834627776}}</ref>
* ''A Guide for Machine Vision in Quality Control'' (Anand and Priya, 2019)<ref>{{Cite book|last=ANAND|first=SHEILA. PRIYA, L.|date=2020|url=https://www.worldcat.org/oclc/1134514667|title=A guide for machine vision in quality control|location=[Place of publication not identified]|publisher=CRC Press|isbn=978-1-000-75381-3|oclc=1134514667}}</ref>
 
== Referensi ==
<references />
 
[[Kategori:Teknologi]]
[[Kategori:Teknik Mesinmesin]]
[[Kategori:Teknik Elektroelektro]]
[[Kategori:VisiPenglihatan mesin]]
[[Kategori:Mekatronika]]
[[Kategori:Robotika]]
[[Kategori:Otomasi industri]]
Diperoleh dari "https://wiki-indonesia.club/wiki/Penglihatan_mesin"