Real-Time Resistor Color Code Recognition using Image Processing in Mobile Devices

  • Yazar/lar DEMİR, Muhammed Fatih
    ÇANKIRLI, Ayşenur
    KARABATAK, Begüm
    YAVARIABDI, Amir
    MENDİ, Engin
    KUSETOĞULLARI, Hüseyin
  • Yayın Türü Konferans Bildirisi
  • Yayın Tarihi 2018
  • DOI Numarası 10.1109/IS.2018.8710533
  • Yayıncı Institute of Electrical and Electronics Engineers Inc.
  • Tek Biçim Adres http://hdl.handle.net/20.500.12498/2865

This paper proposes a real-time video analysis algorithm to read the resistance value of a resistor using a color recognition technique. To achieve this, firstly, a nonlinear filtering is applied to input video frame to smooth intensity variations and remove impulse noises. After that, a photometric invariants technique is employed to transfer the video frame from RGB color space to Hue-Saturation-Value (HSV) color space, which decreases sensitivity of the proposed method to illumination changes. Next, a region of interest is defined to automatically detect resistor's colors and then an Euclidean distance based clustering strategy is employed to recognize the color bars. The proposed method provides a wide range of color classification which includes twelve colors. In addition, it utilizes relatively low computational time which makes it suitable for real-time mobile video applications. The experiments are performed on a variety of test videos and results show that the proposed method has low error rate compared to the other resistor color code recognition mobile applications. © 2018 IEEE.

  • Koleksiyonlar
Erişime Açık
Görüntülenme
4
22.03.2024 tarihinden bu yana
İndirme
1
22.03.2024 tarihinden bu yana
Son Erişim Tarihi
19 Nisan 2024 14:25
Google Kontrol
Tıklayınız
Tam Metin
Tam Metin İndirmek için tıklayın Ön izleme
Detaylı Görünüm
Eser Adı
(dc.title)
Real-Time Resistor Color Code Recognition using Image Processing in Mobile Devices
Yayın Türü
(dc.type)
Konferans Bildirisi
Yazar/lar
(dc.contributor.author)
DEMİR, Muhammed Fatih
Yazar/lar
(dc.contributor.author)
ÇANKIRLI, Ayşenur
Yazar/lar
(dc.contributor.author)
KARABATAK, Begüm
Yazar/lar
(dc.contributor.author)
YAVARIABDI, Amir
Yazar/lar
(dc.contributor.author)
MENDİ, Engin
Yazar/lar
(dc.contributor.author)
KUSETOĞULLARI, Hüseyin
DOI Numarası
(dc.identifier.doi)
10.1109/IS.2018.8710533
Atıf Dizini
(dc.source.database)
Scopus
Yayıncı
(dc.publisher)
Institute of Electrical and Electronics Engineers Inc.
Yayın Tarihi
(dc.date.issued)
2018
Kayıt Giriş Tarihi
(dc.date.accessioned)
2020-08-07T12:52:37Z
Açık Erişim tarihi
(dc.date.available)
2020-08-07T12:52:37Z
Kaynak
(dc.source)
9th International Conference on Intelligent Systems, IS 2018
ISSN
(dc.identifier.issn)
9781538670972 (ISBN)
Özet
(dc.description.abstract)
This paper proposes a real-time video analysis algorithm to read the resistance value of a resistor using a color recognition technique. To achieve this, firstly, a nonlinear filtering is applied to input video frame to smooth intensity variations and remove impulse noises. After that, a photometric invariants technique is employed to transfer the video frame from RGB color space to Hue-Saturation-Value (HSV) color space, which decreases sensitivity of the proposed method to illumination changes. Next, a region of interest is defined to automatically detect resistor's colors and then an Euclidean distance based clustering strategy is employed to recognize the color bars. The proposed method provides a wide range of color classification which includes twelve colors. In addition, it utilizes relatively low computational time which makes it suitable for real-time mobile video applications. The experiments are performed on a variety of test videos and results show that the proposed method has low error rate compared to the other resistor color code recognition mobile applications. © 2018 IEEE.
Yayın Dili
(dc.language.iso)
en
Tek Biçim Adres
(dc.identifier.uri)
http://hdl.handle.net/20.500.12498/2865
Analizler
Yayın Görüntülenme
Yayın Görüntülenme
Erişilen ülkeler
Erişilen şehirler
6698 sayılı Kişisel Verilerin Korunması Kanunu kapsamında yükümlülüklerimiz ve cerez politikamız hakkında bilgi sahibi olmak için alttaki bağlantıyı kullanabilirsiniz.

creativecommons
Bu site altında yer alan tüm kaynaklar Creative Commons Alıntı-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.
Platforms