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Real-Time Resistor Color Code Recognition using Image Processing in Mobile Devices
Karatay Üniversitesi, TUR.
Karatay Üniversitesi, TUR.
Turkcell, Nicosia, CYP.
Karatay Üniversitesi, TUR.
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2018 (English)In: 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings / [ed] JardimGoncalves, R; Mendonca, JP; Jotsov, V; Marques, M; Martins, J; Bierwolf, R, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 26-30Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2018. p. 26-30
Keywords [en]
Android platform, Color recognition, Decision making, Image and video processing, Resistor classification, Bar codes, Color, Color codes, Computation theory, Image segmentation, Impulse noise, Intelligent systems, Resistors, Video signal processing, Android platforms, Hue saturation values, Intensity variations, Photometric invariants, Real-time mobile video, Real-time video analysis, Color image processing
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-18025DOI: 10.1109/IS.2018.8710533ISI: 000469337900005ISBN: 9781538670972 (print)OAI: oai:DiVA.org:bth-18025DiVA, id: diva2:1324920
Conference
9th International Conference on Intelligent Systems, IS 2018; Funchal - Madeira; Portugal; 25 September 2018 through 27 September
Available from: 2019-06-14 Created: 2019-06-14 Last updated: 2019-07-01Bibliographically approved

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Kusetogullari, Hüseyin

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