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Cross-arms Identification with Adaptive Digital Image Processing

by Jose F. R. Da Silva, Ruy A. C. Altafim, andre R. Hirakawa
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 23
Year of Publication: 2015
Authors: Jose F. R. Da Silva, Ruy A. C. Altafim, andre R. Hirakawa
10.5120/21843-5118

Jose F. R. Da Silva, Ruy A. C. Altafim, andre R. Hirakawa . Cross-arms Identification with Adaptive Digital Image Processing. International Journal of Computer Applications. 121, 23 ( July 2015), 36-39. DOI=10.5120/21843-5118

@article{ 10.5120/21843-5118,
author = { Jose F. R. Da Silva, Ruy A. C. Altafim, andre R. Hirakawa },
title = { Cross-arms Identification with Adaptive Digital Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 23 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 36-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number23/21843-5118/ },
doi = { 10.5120/21843-5118 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:09:14.745141+05:30
%A Jose F. R. Da Silva
%A Ruy A. C. Altafim
%A andre R. Hirakawa
%T Cross-arms Identification with Adaptive Digital Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 23
%P 36-39
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an adaptive digital image processing algorithm to improve the identification and classification process of wood cross-arms in the context of automated image inspection robot for distribution power lines. Processing of images that come from outdoor environment is a very difficult task due to the interference of variation of lightning conditions, especially over non uniform objects like wood cross-arms. Usual approaches take advantage of threshold and reference variation in accordance to the best condition to extract desired image object. The proposed adaptive algorithm is based on the Adaptive Digitized Straight Line Segments (ADSLS) that sum up the capability of dynamic change of image segmentation process like binarization and contour extraction. Proposed algorithm was tested on the identification and classification of different type of wood cross-arm with polyurethane protective treatment and results shown improvement in the image segmentation process.

References
  1. Brown, RE. Electric Power Distribution Reliability. New York: Marcel Dekker, 2002.
  2. Short, TA. Electric Power Distribution Handbook. Florida: CRC Press, 2004.
  3. Pavani, RA. , Scaff, W. , Miguel, DS. , Matsumura, CT. , Hirakawa, AR. , Horikawa, O. , Silva, JFR. Double conical wheels based mobile robot for aerial power distribution lines inspection. In Proceedings of the 3rd International Conference on Applied Robotics for the Power Industry (CARPI), pp. 1-6, 2014.
  4. Silva, JFR. Relatório Técnico sobre vida útil de cruzetas em sistemas de Distribuição de Energia. Campinas, Brasil: Eletricidade e Serviços S. A (ELEKTRO), 2001; (in Portuguese).
  5. Asböll, E. Laminated wood structures in Norwegian Transmission Lines. Proceedings of the International Conference on Overhead Line Design and Construction: Theory and Practice, 1998.
  6. Liebel SA. and Mueller RE. Douglas Fir Cross-arms Solid Sawn vs. Laminated Comparison, Transmission and Distribution Conference, Proceedings of the IEEE Power Engineering Society, 1994.
  7. BRAZILIAN STANDARD. NBR 7190, on Project of Wood Structures, 1997.
  8. Altafim, RAC. , Silva, JFR. , Gonzaga, DP. , Ribeiro, C. , Godoy, J. , Basso, HC. , Bueno, B. , Calil Júnior, C. , Sartori, JC. , Altafim, RAP. , Silveira, A. Wood Cross-arms Coated with Polyurethane Resin – Tests and Numerical Simulations. Materials Research, Vol. 9, No. 1, pp. 77-81, 2006.
  9. Queiroz, LCL. , Hirakawa, AR. Classification of Baumann samples through digital image processing. Tecnologia em Metalalurgia Materiais e Mineração, Vol. 10, No. 2, pp. 183-189, 2013.
  10. Hirakawa, AR. , Amancio, SM. , Saraiva, AM. , Cugnasca, CE. , Correia, PL. ViBee - Video segmentation applied to reduce video bitrates in bee weblabs. Exacta, Vol. 7, No. 1, pp. 99-107, 2009.
  11. Barros Neto, LC. , Hirakawa, AR. , Massola, AMA. Adaptive Modeling of Digital Straightness Applied to Geometric Representation Enhancement. International Journal of Computer Applications, Vol. 10, No. 2, pp. 31-39, 2010.
  12. Brons, R. Linguistic methods for the description of a straight line on a grid. Computer Graphics and Image Processing, Vol. 3, No. 1, pp. 48-62, 1974.
  13. Klette, RA. and Rosenfeld, AB. Digital straightness – a review. Discrete Applied Mathematics, Vol. 139, No. 1-3, pp. 197-230, 2004.
  14. Kiryati, N. and Kübler, O. Chain code probabilities and optimal length estimators for digitized three- dimensional curves. Pattern Recognition, Vol. 28, No. 3, pp. 361-372, 1995.
  15. Rosenfeld, A. Digital straight line segments. IEEE Transactions on Computers, Vol. 23, No. 12, pp. 1264-1269, 1974.
  16. Dorst, L. and Smeulders, AWM. Discrete straight line segments: Parameters, primitives and properties. Vision Geometry, series Contemporary Mathematics, American Mathematical Society, Vol. 119, pp. 45-62, 1991.
  17. Freeman, H. Boundary encoding and processing. Picture Proceedings and Psychopictorics, pp. 241-266, 1970.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Digital Image Processing ADSLS

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