Ni shi na cikin kwayoyin signal-to-noise? Ana yi aiki don wani daga cikin Embedded Vision?

Ana gane a ce kawai kuna iya fahimta makontri na cikinƙasa na signal-to-noise ratio (SNR)? Wani da aka yi shirinwa su sanimai masu watsalarwa bata zai iya fahimta anan daidaita systemarwa ne daga kamatawa na kamera na sensors da aka yi amfani da ido na rubutuwa da video data, ya kamatawa da bayyana da gabatarwa a cikin yaminsa, ya kan tabbatarwa a cikin sabon rayuwar wannan systemarwa. Cikinƙasa na signal-to-noise ratio ne factor na farin kasance da aka zo ta taimakon rubutuwa, hanyoyi da performance.

Kadai kuna still daga samarun cikinƙasa na signal-to-noise ratio. Kawai kuna iya labararwa, kuna bai iya fahimta ma'ana, ake kira, da wannan a nemo important. A cikin wannan rubutuwa, suna za'a yi amfani da wannan aiki a cikin sanimai masu watsalarwa (masaka smart surveillance cameras, automatic carry-over photography, etc.).

An jin cikinƙasa na Signal-to-Noise Ratio?

man shi SN ratio? Kwayoyin gaba-gaban tare da kwayoyin, amma SNR suna ke shi, yana jama'a mai sauran kwayoyin a cikin wannan kwayoyin na samun relative to the background noise (kwayoyin baya). SNR ya kamatawa don samun kwayoyin a cikin wannan kwayoyin da kwayoyin baya a system, zamu iya samun kwayoyin different outputs, da ido da aka yi daga wannan kwayoyin.

Kwayoyin gaba-gaban tare da kwayoyin baya yana iya yi amfani da decibels (dB). Wannan lokacin da kwayoyin gaba-gaban tare da kwayoyin baya ya so, ya kamatawa wannan kwayoyin. A vision embedded, kwayoyin ya ne data yanu a ciki device, ya magana information system ya kamatawa process. Kwayoyin baya ya magana electromagnetic interference, vibration, da hanyar binciken. Wannan lokacin da kwayoyin baya ya so, ya kamatawa wannan kwayoyin, ya kamatawa wannan kwayoyin, ya kamatawa wannan kwayoyin, ya kamatawa wannan kwayoyin.

ake kwayoyi da ya fi? Kwayoyin abubuwa na rayuwa a cikin rubutuwa (SNR) yana iya yi aiki don wani rubutun, da aka yi amfani da decibels:

s/n ratio formula: SNR = 20 * log10 (Matsakaicin Sigina / Matsakaicin Hayaniya)

Nuna rubutun yana sama sunan intensiti na fayilin image ko video, saman bayan na noise yana sama intensiti na noise an yi aiki don bayan.

An yi shi mai gaba rubutuwa na rayuwa a cikin vision na gabatarwa?

Rubutuwa na rayuwa yana importance kuma kawai kwanan kuma kaiwarka na quality na image da video bayan, da accuracy ne reliability na result na analysis. A matsayin application na vision na gabatarwa, misali edge processing, saman head counting da object recognition, SNR na gaba yana ba haɗi a cikin reduction na noise particles a cikin image da kuma yana bincika result. Da a matsayin algorithm saman machine learning da artificial intelligence, SNR na gaba yana iya yi amfani da accuracy na data processing da kuma reduce errors. Kuma a matsayin camera modules na low-light , yana iya yi amfani da reflection na gaba na noise a cikin quality na image.

Impact na noise a cikin vision na gabatarwa bayan

Kasa mai alamna yana kula daidai ta tsaye daga rubutu na cikin shafi ko video, misali takardun, kasa kwanan taimaka, pixelation, da co, ake soya gabatar daidai. Suna kasance wannan kasanci ya kamata masu samar daidai da aka samu, ya kamata masa systeme ne ke yi amfani da wani makon gaba. Ya kamata da sabunta da rubutun haɗaɗen daidai. An yi binciken kasa don vision tunƙa?

Tsunfa da Kasance Kasa (SNR) don Tsarin Systeme Vision Tunƙa

Makon kasa: Kasance SNR kamar lafiya ya saukar kasance, ya kamata masa systeme ne ke samu makon gaba daga inforɓanci.
Dabar Daidai: Makon SNR ya zama hanyar dabar daidai na systeme, yayyin rubutu bayan labari da labari daidai. Kasance SNR kamar lafiya ya kamata masa systeme ne ke samu farko da farko.
Kawo da Tsarin: SNR na gaba yana saukar da aikin samfara wanda, kuma SNR na kula yana sosai da kawo da tsarin da hannun cikin rubutu, ya yi daga wannan hanyoyi mai amfani da alamar daidaita edge detection.

Yadda ne jinsi da SNR yanuwar da camerar?

SNR bane sosai da aiki da visualization, wanda yana rabin daidaita da cikakken camerar. Fahimta jinsi da cikakken camerar yanuwa da SNR yana sosai da wannan hakuri mai shirye.

Dabar Daidai: Dynamic range na daidai yana kawo da sabon rangar littafin, wanda yana haifar da SNR na daidai cikin wasu levels tsauni, kuma sosai da fahimtar daidai cikin rubutun tsauni da gabatarwa.

ISO Sensitivity: ISO na kula yana sosai da signal kuma sosai da zama, ya sosai da SNR. ISO na gaba yana sosai da sound to noise ratio, kuma yana samun hanyar daidai da light for exposure.

Shutter speed: kungiyar shafa a cikin rubutu suna zuba daga hanyar daidaita, amma ya kamar yanzu wajen gaba ko ISO, yayi aiki daga hanyar SNR. rubutu na shafi daga cikin tsaunin tara daidai ya yi wani hanyar SNR ta fiye daga hanyar rubutu.

Sai Zambonƙi: da ni sensor yana kashewa, da ni pixel-ziya yana kashewa, da ni fitini da aka jama'a da wannan rayuwar tsohon da aka samfura daidai a cikin wannan tsohon-tarabarba. A matsayi, pixels na tare da ke sauka daidai da aka samfura daidai a cikin tsohon-tarabarba.

Algoritamai na samar daidai: Algoritamai na samar daidai mai tsarin daidai ya kawai daidai mai sauka daidai a cikin tsohon-tarabarba samun samar daidai.

Hanyar gaba: Da ni gaba yana kashewa, da ni rayuwar tsohon yana kashewa, ya kawo daidai a cikin samun tsohon-tarabarba. Da ni gaba yana tare da, da ni hanyar rubutu yana kashewa, ya yi daidai mai sauka daidai.

Ana so rubutu a cikin hanyar rubutu an yi aiki daga hanyar SNR?

Wata daidai ne yanzu a cikin abubuwa na gaba, an yi amfani da wata daidai na sensor za'a koma harshe. Wata daidai naɗanƙwar daidai suna zai buga shirin tsarin wannan daidai, tebarka'a ya kamata aiki daidai da gabatar daidai. Da fatan ya zai buga gabatar daidai na harshen photonic da electronic, mai tabbatar da suka samun harshe kuma a cikin wata daidai naɗanƙwar daidai, ya kan yi baton da shirin fayil.

Daga cikin wannan, mutum ake sonkarar da signal (s) ya kamata aiki da idaka da idaka na hannun photon suka buga daga cikin wata daidai naɗanƙwar daidai, wannan ya kamata aiki da product dai dai na hannun harshe (I) da wata daidai naɗanƙwar daidai (t):

Da fatan ya kawo amfani da hannun photon, gabatar daidai na photon scattering (gabatar daidai na photon scattering ya kamata aiki da gabatar daidai mai tabbatar da suka samun system mai tabbatar da aka yi amfani da hannun harshe a matsayi units (ya karfi, photons)) ya zama. Gabatar daidai na gaba da signal-to-noise ratio tare da photon scattering noise (SNR_Shot) ya kamata aiki da wannan rubutu:

Kuna a cikin tsari da kasa ya soja, jarabun photons dai dai (N) ya soji, kuma shi a signal (S). Gaba na sabon gida na signal (√S) ya soji. Suna ne kawai da cikin kasancewar da kasa ya soja, rubutuwa na signal lafiya soji da sabon gida na tsari.

Sunan sugunan wani aiki daga wannan suka yi aiki da rubutuwa na signal lafiya

Daga cikin yadda suka zai iya samun, sunan nan na iya samun aiki da rubutuwa na signal lafiya amfani da kawo rubutuwa na signal lafiya. don haka suna suka zai iya samun sugunan wani aiki daga wannan:

• don aiki da signal. Kana baya aiki da over-optimization don baya aiki da amplifying da rubutuwa, kamar kawai da cikin rubutuwa na fayilu.
• Aiki da architecture na kamara kuna a cikin samun or customizing da kamara. Aikin da architecture na design mai kyau kuna a cikin samun performance na imaging mai kyau.
• Aiki da sensor na kwalite mai kyau. Sensors na image na kwalite mai kyau da readout noise na rubutuwa mai kyau kuna a cikin samun rubutuwa na signal lafiya.
• Taswira daidai na hanyar kula yana soya waniyya sensor da kawai shirin gari-gari mai tsaye a cikin kuma ga wannan sunan tsohon gari-gari mai tsaye.
• yanuwarwa daidai na rubutuƙen camera tomutane rubutun exposure time da speed na shutter don soya gari-gari mai tsaye saman saman yana bincika wannan rubutu.

Don labararwa

Rubutun signal-to-noise ratio ya ne factor daidai ya fiye masu rubutuwa daga system na vision embedded, ya che daidai ya fadi da shirin rubutun image da video data da daidai na accuracy da reliability na result na analysis. Suna za'a iya sami labararwa daidai na rubutun signal-to-noise ratio, factor na rubutuwa, da daidai na wayarwa don soya, don ake samun system na vision embedded masu daidai da aka yi labararwa daidai.

Idan ka kara sosai amfani ba da customize camera na gari-gari mai tsaye da idinka integrate shi a cikin application na vision embedded, zaka iya karatu kunna Mana .