Skip to main content
SpringerLink
Log in

One Rapid Segmentation Algorithm for Quasi-circular Fruits

  • Chapter
  • First Online:
Recent Advances in Computer Science and Information Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 128))

Abstract

Image segmentation algorithm is an important step in image pattern recognition process, and it is also important in the fruit identification. Against the adjacent fruits are quasi circular, proposed diameter circular template segmentation algorithm. This segmentation algorithm is simple and processes fast. It is a block-based image segmentation algorithm. Fruit segmentation experiments show that the algorithm can quickly and efficiently divide the non-overlapping round fruits.

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 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Lin, K.: A Survey on Color Image Segmentation Technique. Journal of Image and Graphics 10(1), 1–9 (2005)

    Google Scholar 

  2. Zheng, X.: A Survey of New Image Segmentation Methods. Computer and Mathematics Engineering 35(8), 103–106 (2007)

    Google Scholar 

  3. Milind, M., Mushrif, A., Ray, K.: Color image segmentation: Rough set theoretic approach. Pattern Recognition Letters 10 (2007)

    Google Scholar 

  4. Liu, H., Wang, M.: Method for classification of apple surface defect based on digital image processing. Transactions of the CSAE 20(6), 138–140 (2004)

    Google Scholar 

  5. Blasco, J., Aleixos, N., Molto, E.: Machine Vision System for Automatic Quality Grading of Fruit. Biosystems Engineering 85(4), 415–423 (2003)

    Article  Google Scholar 

  6. Zhang, T.: Object extraction for the vision system of fruit picking robot. Journal of China Agricultural University 9(2), 68–72 (2004)

    Google Scholar 

  7. Li, S., Tan, Y.: An Image Fully Thinning Algorithm Based on Spanning Tree. Computer Engineering and Design 11(27), 4006–4007 (2006)

    Google Scholar 

  8. Li, S., Tan, Y.: Colony Biologic Object Position Based on Color Space Model. Computer Engineering and Design 10(28), 4964–4967 (2007)

    Google Scholar 

  9. Luo, S.: A new method of recognizing quasi circular object. Journal of Central South University 35(4), 632–637 (2004)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Yunnan Electronic Computation Center, Yunnan University, 2 North Cuihu Road, 650091, Kunming, Yunnan, China

    Li Su & Tan Yonglong

Authors
  1. Li Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tan Yonglong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Li Su .

Editor information

Editors and Affiliations

  1. , College of Communication Engineering, Jilin University, Room 313, Building No.1, Changchun, Nanhu Avenue 5372, Jilin, 130012, China, People's Republic

    Zhihong Qian

  2. , Department of Electrical Engineering, The University of Mississippi, Anderson Hall 314, Mississippi, 38677, Mississippi, USA

    Lei Cao

  3. , Department of Electrical and Computer En, Naval Postgraduate School, Rm. 452 Spanagel Bldg. 232, Dyer Road 833, Monterey, 93943-5121, California, USA

    Weilian Su

  4. , Faculty of Computing, London Metropolitan University, Holloway Road 166-220, London, N7 8DB, United Kingdom

    Tingkai Wang

  5. , College of Software, Changchun University of Science and Tech, Changchun, Jilin, 130022, China, People's Republic

    Huamin Yang

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag GmbH Berlin Heidelberg

About this chapter

Cite this chapter

Su, L., Yonglong, T. (2012). One Rapid Segmentation Algorithm for Quasi-circular Fruits. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25792-6_44

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25792-6_44

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25791-9

  • Online ISBN: 978-3-642-25792-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation