Penglihatan mesin: Perbedaan antara revisi

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[[Berkas:Machine Vision System.jpg|jmpl|Salah satu penerapan sistem visi mesin pada [[Lini perakitan|jalur (line) produksi ban berjalan (conveyor belt)]]]]
Secara umum, visi 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 visi mesin adalah [[MATLAB|Matlab]].<ref name=":0" /><ref name=":1" />
 
Aplikasi dari visi 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]].
 
== 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 visi mesin]]
Secara umum, visi 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/ kabur]], [[Vektor satuan|vektor]] (terutama ''[[Support-vector machine|support vector machines]]''), dan [[Analisis numerik|komputasi/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 visi mesin.]]
Secara umum, kerja dari sistem visi mesin menyerupai kerja dari blok diagram [[Sistem kendali|kendali]] secara umum di mana terdapat masukan/input, pengolahan data, serta output/keluaran.
 
=== Input/Masukan ===
[[Histogram]]Masukan sendiriatau digunakaninput diyang dalamakan analisisdiolah pikseloleh darisistem citrasendiri ditangkap oleh alat berupa [[sensor]] atau gambar[[kamera]] yang digunakanakan sebagaimenangkap masukan/inputcitra atau gambar dari sistemobjek yang akan diolah pirantioleh lunakaktuator.
 
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 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/ kabur]], serta algoritma genetik mulai digunakan. Sementara, untuk matriks, secara umum sistem visi 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> 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=":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 piranti lunak.
[[Berkas:African Cape Daisy (tresholded).svg|jmpl|Salah satu contoh hasil pengambangan pada bunga daisy (African Cape). Sistem visi 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.
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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/[[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 ukuran [[umbi]].<ref>{{Cite journal|last=ElMasry|first=Gamal|last2=Cubero|first2=Sergio|last3=Moltó|first3=Enrique|last4=Blasco|first4=José|date=2012-09|title=In-line sorting of irregular potatoes by using automated computer-based machine vision system|url=https://linkinghub.elsevier.com/retrieve/pii/S0260877412001690|journal=Journal of Food Engineering|language=en|volume=112|issue=1-2|pages=60–68|doi=10.1016/j.jfoodeng.2012.03.027}}</ref>
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=== 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 ===
Baris 47 ⟶ 53:
[[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>
 
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>
 
=== 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>
 
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 Jalurjalur Kedatangankedatangan.<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 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>
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Beberapa bahan bacaan yang dapat dirujuk terkait sistem visi mesin:
 
* ''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>
* ''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>
 
== Referensi ==