Skip to main content
SpringerLink
Log in

Analysis of Segmentation and Identification of Square-Hexa-Round-Holed Nuts Using Sobel and Canny Edge Detector

  • Conference paper
  • First Online:
Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1037))

Abstract

In the existing real-time automobile shop, it is difficult to trace an object and identify its presence. The failure may happen due to its absence or improper match of shape as its identity. So to overcome this, we propose a method which can be used for the automatic identification of vehicular nuts based on the input image that contains a nut with square, hexa, rounded-head and pinned-bolt shapes. The application even works with the nut having clear view or any entity added like mud, noise, colour, etc. on the surface of nut. For the identification process the database has been designed to store different shapes for selected number of nut-shapes. By applying median filter during pre-processing stage, the Sobel-edge-detector and Canny-edge-detector; segmented and identified the captured images by identifying the edges to ascertain shape of the input. With the experimentations carried the method results with an accuracy of 86.1875%

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Hosur, R., Savakar, D.G., Madabhavi, S.: Shape based object retrieval technique for vehicular spare parts. Int. J. Eng. Technol. (UAE) 7(4.5), 355–359 (2018)

    Article  Google Scholar 

  2. Santosh, K.C., Roy, P.P.: Arrow detection in biomedical images using sequential classifier. Int. J. Mach. Learn. Cybern. 9(6), 993–1006 (2018)

    Article  Google Scholar 

  3. Savakar, D.G., Hosur, R.: A relative 3D scan and construction for face using meshing algorithm. Multimedia Tools Appl. 77(19), 25253–25273 (2018)

    Article  Google Scholar 

  4. Santosh, K.C., Aafaque, A., Antani, S., Thoma, G.R.: Line segment-based stitched multipanel figure separation for effective biomedical CBIR. Int. J. Pattern Recogn. Artif. Intell. (IJPRAI) 31(6), 1–18 (2017)

    Google Scholar 

  5. Zohora, F.T., Santosh, K.C.: Foreign circular element detection in chest X-rays for effective automated pulmonary abnormality screening. Int. J. Comput. Vis. Image Process. (IJCVIP) 7(2), 36–49 (2017)

    Article  Google Scholar 

  6. Zohora, F.T., Santosh, K.C.: Circular foreign object detection in chest X-ray images. In: Santosh, K.C., Hangarge, M., Bevilacqua, V., Negi, A. (eds.) RTIP2R 2016. CCIS, vol. 709, pp. 391–401. Springer, Singapore (2017). https://doi.org/10.1007/978-981-10-4859-3_35

    Chapter  Google Scholar 

  7. Santosh, K.C., Vajda, S., Antani, S., Thoma, G.R.: Edge map analysis in chest X-rays for automatic abnormality screening. Int. J. Comput. Assist. Radiol. Surg. (IJCARS) 11(9), 1637–1646 (2016)

    Article  Google Scholar 

  8. Santosh, K.C., Candemir, S., Jaeger, S., Karargyris, A., Antani, S., Thoma, G.: Automatically detecting rotation in chest radiographs using principal rib-orientation measure for quality control. Int. J. Pattern Recogn. Artif. Intell. (IJPRAI) 29(2), 1557001 (2015)

    Article  MathSciNet  Google Scholar 

  9. Candemir, S., Borovikov, E., Santosh, K.C., Antani, S., Thoma, G.: RSILC: Rotation- and Scale-Invariant, Line-based Color-aware descriptor. Image Vis. Comput. 42, 1–12 (2015)

    Article  Google Scholar 

  10. Herrera, J.L., del-Blanco Narciso Garcia, C.R.: Edge based depth gradient refinement for 2D to 3D learnt prior conversion. In: IEEE 3DTV-Conference: The True Vision-Capture, Transmission and Display of 3D Video (3DTV-CON) (2015)

    Google Scholar 

  11. Wu, Z., Li, J., Hu, J., Deng, W: Pose-invariant face recognition using 3D multi-depth generic elastic models. IEEE (2015)

    Google Scholar 

  12. Zhou, Y., Guo, H., Fu, R., Liang, G., Wang, C., Wu, X.: 3D reconstruction based on light field information. In: Proceeding of the 2015 IEEE International Conference on Information and Automation Lijiang, Held on August 2015

    Google Scholar 

  13. Kaneko, M., Hasegawa, T., Yamauchi, Y., Yamashita, T., Fujiyoshi, H., Murase, H: Fast 3D edge detection by using decision tree from depth image. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Congress Center Hamburg, Hamburg, Germany, 28 September–2 October 2015, pp. 1314–1319 (2015)

    Google Scholar 

  14. Xu, X., et al.: Adaptive block truncation filter for MVA depth image enhancement. In: 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP) (2014)

    Google Scholar 

  15. Singh, M., Sharma, R., Garg, D.: A new proposed issue for secure image steganography technique based on 2D block DCT and DCT. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 2, 29–33 (2012)

    Google Scholar 

  16. Izadi, S., et al.: KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera. In: UIST 2011 (2011)

    Google Scholar 

  17. Alptekin Engin, M., Cavsoglu, B.: New approach in image compression: 3D spiral JPEG. IEEE Commun. Lett. 15(11), 1234–1236 (2011)

    Article  Google Scholar 

  18. Khare, A., Kumari, M., Khare, P.: Efficient algorithm for digital image steganography. J. Inf. Knowl. Res. Comput. Sci. Appl. 1(1), 1–5 (2010)

    Google Scholar 

  19. Bariya, P., Nishino, K.: Scale-hierarchical 3D object recognition in cluttered scenes. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1657–1664 (2010)

    Google Scholar 

  20. Yu, Z., Ip, H.H.S., Kwok, L.F.: A robust watermarking scheme for 3D triangular mesh models. J. Pattern Recogn. Soc. 36(11), 2603–2614 (2003)

    Article  Google Scholar 

  21. Zhang, D., Lu, G.: Shape based image retrieval using Generic Fourier Descriptor. J. Sig. Process. Image Commun. 17(10), 825–848 (2002)

    Article  Google Scholar 

  22. Zhang, D., Lu, G.: A comparative study of curvature scale shape and Fourier descriptors for shape-based image retrieval. J. Vis. Commun. Image Represent. 14(1), 39–57 (2003)

    Article  Google Scholar 

  23. Liu, Y., Zhang, D., Lu, G., Ma, W.-Y.: A survey of content-based image retrieval with high-level semantics. J. Pattern Recogn. 40(1), 262–282 (2007)

    Article  Google Scholar 

  24. Krishnan, N., Varghese, J., Saudia, S., Mathew, S.P., et al.: A new adaptive class of filter operators for salt and pepper impluse corrupted images. Int. J. Imaging Sci. Eng. (IJISE) 1(2), 44–51 (2007)

    Google Scholar 

  25. Peng, S.-H., Kim, D.-H., Lee, S.-L., Chumg, C.-W.: A visual shape descriptor using sectors and shape context of contour lines. J. Inf. Sci. 180(16), 2925–2939 (2010)

    Article  Google Scholar 

  26. Wang, X.-Y., Yu, Y.-J., Yang, H.-Y.: An effective images retrieval scheme using color, texture and shape features. J. Comput. Stand. Interfaces 33, 59–68 (2010)

    Article  Google Scholar 

  27. Rao, S., Srinivas Kumar, S., Chandra Mohan, B.: Content-based image retrieval using exact legendre moment and support vector machine. Int. J. Multimedia Appl. 2(2), 69–79 (2010)

    Article  Google Scholar 

  28. Mathew, S.P., Balas, V.E., Zachariah, K.P., Samuel, P.: A content-based image retrieval system based on polar raster edge sampling signature. Acta Polytech. 11(3), 25–36 (2014)

    Google Scholar 

  29. Nanni, L., Lumini, A., Brahnam, S.: Ensemble of shape descriptors for shape retrieval and classification. Int. J. Adv. Intell. Paradigms (IJAIP) 6(2), 136–156 (2014)

    Article  Google Scholar 

  30. Ruikar, D.D., Santosh, K.C., Hegadi, R.S.: Automated fractured bone segmentation and labeling from CT images. J. Med. Syst. (2019). https://doi.org/10.1007/s10916-019-1176-x

    Article  Google Scholar 

  31. Ruikar, D.D., Santosh, K.C., Hegadi, R.S.: Segmentation and analysis of CT images for bone fracture detection and labeling. In: Medical Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques, Chap. 7. CRC Press (2019). ISBN 9780367139612

    Google Scholar 

  32. Hegadi, R.S., Navale, D.I., Pawar, T.D., Ruikar, D.D.: Multi feature-based classification of osteoarthritis in knee joint X-ray images. In: Medical Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques, Chap. 5. CRC Press (2019). ISBN 9780367139612

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Rani Chennamma University, Torvi, Vijayapur, Karnataka, India

    Dayanand G. Savakar

  2. BLDEA’s V. P. Dr. P. G. Halakatti College of Engineering and Technology, Vijayapur, Karnataka, India

    Ravi Hosur & Deepa Pawar

Authors
  1. Dayanand G. Savakar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ravi Hosur
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Deepa Pawar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ravi Hosur .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Savakar, D.G., Hosur, R., Pawar, D. (2019). Analysis of Segmentation and Identification of Square-Hexa-Round-Holed Nuts Using Sobel and Canny Edge Detector. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1037. Springer, Singapore. https://doi.org/10.1007/978-981-13-9187-3_24

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-9187-3_24

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9186-6

  • Online ISBN: 978-981-13-9187-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation