Visual extraction system for insulators on power transmission lines from UAV photographs using support vector machine and color models


In this paper, a system is proposed for extracting insulators on power transmission lines from photographs captured by an unmanned aerial vehicle. The approximate regions of the insulators are first determined by a support vector machine with the histogram of oriented gradients as the feature descriptor. Then, the specific regions of insulators are detected and extracted by the GrabCut algorithm. In advance, some constraint conditions, such as the value ranges of color component values as well as the relationships between the component values in three color models, need to be specified. In our system, an interactive interface is developed to help determine these conditions. According to the experimental results, our system is capable of removing most of the backgrounds and extracting the insulators from photographs.

Graphical abstract

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9


  1. Abdulla W (2017) Mask r-cnn for object detection and instance segmentation on keras and tensorflow.

  2. Carpineto C, Michini C, Nicolussi R (2009) A concept lattice-based kernel for SVM text classification. In: International conference on formal concept analysis. Springer, pp 237–250

  3. Chapelle O, Haffner P, Vapnik VN (1999) Support vector machines for histogram-based image classification. IEEE Trans Neural Netw 10(5):1055–1064

    Article  Google Scholar 

  4. Chuang J, Weiskopf D, Moller T (2009) Hue-preserving color blending. IEEE Trans Vis Comput Graph 15(6):1275–1282

    Article  Google Scholar 

  5. Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20(3):273–297

    MATH  Google Scholar 

  6. Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society conference on computer vision and pattern recognition, 2005. CVPR 2005., vol 1. IEEE, pp 886–893

  7. Foody GM, Mathur A (2004) A relative evaluation of multiclass image classification by support vector machines. IEEE Trans Geosci Remote Sens 42(6):1335–1343

    Article  Google Scholar 

  8. Fuller A, Zawadzki R, Choi S, Wiley D, Werner J, Hamann B (2007) Segmentation of three-dimensional retinal image data. IEEE Trans Vis Comput Graph 13(6):1719–1726

    Article  Google Scholar 

  9. Goertzel B, Venuto J (2006) Accurate SVM text classification for highly skewed data using threshold tuning and query-expansion-based feature selection. In: International joint conference on neural networks. IEEE, pp 1220–1225

  10. He SY, Wang L, Xia Y, Tang YD (2013) Insulator recognition based on moments invariant features and cascade AdaBoost classifier. Appl Mech Mater 433:362–367

    Article  Google Scholar 

  11. He K, Gkioxari G, Dollár P, Girshick R (2017) Mask r-cnn. In: Proceedings of the IEEE international conference on computer vision, pp 2961–2969

  12. Ibraheem NA, Hasan MM, Khan RZ, Mishra PK (2012) Understanding color models: a review. ARPN J Sci Technol 2(3):265–275

    Google Scholar 

  13. Jain DK, Dubey SB, Choubey RK, Sinhal A, Arjaria SK, Jain A, Wang H (2018) An approach for hyperspectral image classification by optimizing SVM using self organizing map. J Comput Sci 25:252–259

    Article  Google Scholar 

  14. Joachims T (1998) Text categorization with support vector machines: Learning with many relevant features. In: European conference on machine learning. Springer, pp 137–142

  15. Jones MJ, Rehg JM (2002) Statistical color models with application to skin detection. Int J Comput Vis 46(1):81–96

    Article  Google Scholar 

  16. Kashuk S, Iskander M (2015) Evaluation of color space information for visualization of contamination plumes. J Vis 18(1):121–130

    Article  Google Scholar 

  17. Leopold E, Kindermann J (2002) Text categorization with support vector machines. how to represent texts in input space? Mach Learn 46(1–3):423–444

    Article  Google Scholar 

  18. Li W, Ye G, Huang F, Wang S, Chang W (2010) Recognition of insulator based on developed mpeg-7 texture feature. In: 3rd international congress on image and signal processing (CISP), vol 1. IEEE, pp 265–268

  19. Li B, Wu D, Cong Y, Xia Y, Tang Y (2012) A method of insulator detection from video sequence. In: International symposium on information science and engineering (ISISE). IEEE, pp 386–389

  20. Liao S, An J (2015) A robust insulator detection algorithm based on local features and spatial orders for aerial images. IEEE Geosci Remote Sens Lett 12(5):963–967

    Article  Google Scholar 

  21. Lin L, Li BF, Wang L, Cong Y, Tang YD (2013) Faulty insulator diagnosis for UAV videos based on repetitiveness feature. Appl Mech Mater 423:2536–2542

    Article  Google Scholar 

  22. Lin T-Y, Maire M, Belongie S, Hays J, Perona P, Ramanan D, Dollár P, Zitnick CL (2014) Microsoft coco: common objects in context. In: European conference on computer vision. Springer, pp 740–755

  23. Liu Y, Yong J, Liu L, Zhao J, Li Z (2016) The method of insulator recognition based on deep learning. In: 4th International conference on applied robotics for the power industry (CARPI). IEEE, pp 1–5

  24. Lu L, Pei-liang Y, Wei-wei S, Jian-wei M (2017) Similar handwritten chinese character recognition based on CNN-SVM. In: Proceedings of the international conference on graphics and signal processing. ACM, pp 16–20

  25. Naik VA, Desai AA (2017) Online handwritten Gujarati character recognition using SVM, MLP, and K-NN. In: 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, pp 1–6

  26. Nanthagopal AP, Rajamony RS (2012) Automatic classification of brain computed tomography images using wavelet-based statistical texture features. J Vis 15(4):363–372

    Article  Google Scholar 

  27. Nasien D, Haron H, Yuhaniz SS (2010) Support vector machine (SVM) for English handwritten character recognition. In: Second international conference on computer engineering and applications (ICCEA), vol 1. IEEE, pp 249–252

  28. Pérez P, Hue C, Vermaak J, Gangnet M (2002) Color-based probabilistic tracking. In: European conference on computer vision. Springer, pp 661–675

  29. Rother C, Kolmogorov V, Blake A (2004) Grabcut: interactive foreground extraction using iterated graph cuts. ACM Trans Graph 23(3):309–314

    Article  Google Scholar 

  30. Shaik KB, Ganesan P, Kalist V, Sathish B, Jenitha JMM (2015) Comparative study of skin color detection and segmentation in HSV and YCbCr color space. Procedia Comput Sci 57:41–48

    Article  Google Scholar 

  31. Shanthi N, Duraiswamy K (2010) A novel SVM-based handwritten tamil character recognition system. Pattern Anal Appl 13(2):173–180

    MathSciNet  Article  Google Scholar 

  32. Tan C, Hong T, Chang T, Shneier M (2006) Color model-based real-time learning for road following. In: Intelligent transportation systems conference 2006, ITSC’06. IEEE pp 939–944

  33. Wang X, Zhang Y (2016) Insulator identification from aerial images using support vector machine with background suppression. In: International conference on unmanned aircraft systems (ICUAS). IEEE, pp 892–897

  34. Zarit BD, Super BJ, Quek FK (1999) Comparison of five color models in skin pixel classification. In: International workshop on recognition, analysis, and tracking of faces and gestures in real-time systems. IEEE, pp 58–63

Download references


The author (Chi Zhang) appreciates the financial support of China Scholarship Council during his study at Kyoto University.

Author information



Corresponding author

Correspondence to Qing-wu Gong.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhang, C., Gong, Q., Wang, T. et al. Visual extraction system for insulators on power transmission lines from UAV photographs using support vector machine and color models. J Vis (2020).

Download citation


  • Insulator extraction
  • Visualization
  • Support vector machine
  • Color model
  • Image processing
  • Pattern recognition