A Review—Edge Detection Techniques in Dental Images

  • Aayushi AgrawalEmail author
  • Rosepreet Kaur Bhogal
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)


Edge detection plays an important role in digital image processing applications. The main aim of edge detection is to identify the discontinuity in images, where the sharp changes in intensity take place. This research work presents the edge detection technique in dental X-ray images (panoramic radiograms), which is advantageous to separate teeth individually for better classification and identification of diseases. The objective is to study and compare the various algorithms that are Sobel, Prewitt, Canny, multiple morphological gradient (mMG), line analyzer, neural network, genetic algorithm, and infinite symmetric filter (ISF), multi-scale and multi-directional analysis with statistical thresholding (MMST), and fuzzy logic approach for edge detection in dental X-ray images. There are many difficulties in finding diseases from panoramic dental images only, and hence to overcome these difficulties edge detection is introduced. Some of the dental diseases that require edge detection for their identification are discussed. Based on capability of detecting the diseases accurately and total number of diseases detected from the dental images by the use of edge detection, comparison of results takes place.


Edge detection techniques Dental X-ray Dental diseases Fuzzy logic system 


  1. 1.
    Solanki C, Godfrey WW (2016) Technique for edge detection based on interval type-2 fuzzy logic with sobel filtering. In: IEEE transactions. Doi 978-1-5090-1987-8Google Scholar
  2. 2.
    Kaushik A, Mathpal PC, Sharma V (2014) Edge detection and level set active contour model for the segmentation of cavity present in dental X-ray images. Int J Comput Appl 96(9):0975–8887CrossRefGoogle Scholar
  3. 3.
    Senthilkumaran N (2012) Edge detection for dental X-ray image segmentation using neural network approach. Int J Comput Sci Appl (TIJCSA), 1(7)Google Scholar
  4. 4.
    Ansingkar NP, Dhopeshwarkar MG (2014) Study and analysis of edge detection techniques for segmentation using dental radiograph. Int J Eng Comput Sci 3(9)Google Scholar
  5. 5.
    Na`am J, Harlan J, Madenda S, Wibowo EP (2016) The algorithm of image edge detection on panoramic dental X-ray using multiple morphological gradient (mMG) method. Int J Adv Sci Eng Sci Technol 6CrossRefGoogle Scholar
  6. 6.
    Croock MS, Khudhur SD, Taqi AK (2016) Edge detection and features extraction for dental X-ray. Eng Tech J 34 Part (A)(13)Google Scholar
  7. 7.
    Lin PL, Huang P−W, Cho YS, Kuo C−H (2013) An automatic and effective tooth isolation method for dental radiographs. Opto−Electron
  8. 8.
    Saoji SU, Jaini P (2014) Line analyzer techniques for teeth using edge-based method and gray-based method. In: International conference on communication systems and network technologies.
  9. 9.
    Senthilkumaran N (2012) Genetic algorithm approach to edge detection for dental X-ray image segmentation. Int J Adv Res Comput Sci Electron Eng (IJARCSEE) 1(7)Google Scholar
  10. 10.
    Gayathri V, Menon HP (2014) Challenges in edge extraction of dental X-ray images using image processing algorithms—a review in (IJCSIT). Int J Comput Sci Inf Technol 5(4)Google Scholar
  11. 11.
    Pavaloiu I-B, Goga N, Vasilateanu A, Marin I, Ungar A, Patrascu I, Ilie C (2015) Neural network based edge detection for CBCT segmentation. IEEE 978-1-4673-7545-0Google Scholar
  12. 12.
    Mahant PM, Desai NP, Jain KR, Mahan MG (2015) Optimal edge detection method for diagnosis of abscess in dental radiograph. IJRSI II(II)Google Scholar
  13. 13.
    Padma Vasavi K, Udaya Kumar N, Madhavi Latha M, Krihna Rao EV An edge detection scheme for endodontic working length measurement in root canal treatment for succedaneous teeth in latest trends. Circ Syst Sig Process Autom Control. ISBN: 978-960-474-374-2Google Scholar
  14. 14.
    Solanki AJ (2016) Threshold selection in ISEF based identification of dental caries in decayed tooth. Int J Electron Electr Comput Syst (IJEECS) 5(5). ISSN 2348-117XGoogle Scholar
  15. 15.
    Trivedi DN, Shah N, Kothari AM (2016) Dental contour extraction & matching with label contouring using ISEF algorithm on DICOM images for human identification. Int J Latest Trends Eng Technol (IJLTET) 7(2)Google Scholar
  16. 16.
    Pavaloiu I-B, Goga N, Marin I, Vasilateanu A (2015) Automatic segmentation for 3D denta reconstruction. In: ICCCNTGoogle Scholar
  17. 17.
    Kamencay P, Zachariasova M, Hudec R, Benco M, Radil R (2014) 3D image reconstruction from 2D CT slices 3DTV-conference: the true vision—capture, transmission and display of 3D video (3DTVCON)Google Scholar
  18. 18.
    Razali MRM, Ahmad NS, Hassan R, Zaki ZM, Ismail W (2015) Sobel and Canny edges segmentations for the dental age assessment. IEEE. DOI 10.1109Google Scholar
  19. 19.
    Bhargavi K, Jyoth S (2016) An efficient fuzzy logic based edge detection algorithm. Int J Tech Res Appl 4(3)Google Scholar
  20. 20.
    Aborisade DO (2010) Fuzzy logic based digital image edge detection global. J Comput Sci Technol 10(14) (Ver. 1.0)Google Scholar
  21. 21.
    Senthilkumaran N (2012) Fuzzy logic approach to edge detection for dental X-ray image segmentation. (IJCSIT) Int J Comput Sci Inf Technol 3(5)Google Scholar
  22. 22.
    Tangel ML, Fatichah C, Yan F, Betancourt JP, Widyanto RM, Dong F, Hirota K (2013) Dental classification for periapical radiograph based on multiple fuzzy attribute. IEEE 978-1-4799-0348-1Google Scholar
  23. 23.
    Lai YH, Lin PL (2008) Effective segmentation for dental X-ray images using texture- based fuzzy inference system. LNCS 5259:936–947 Google Scholar
  24. 24.
    Moynihan P, Petersen PE (2004) Diet, nutrition and the prevention of dental diseases. Public Health Nutr.
  25. 25.
    Goryawala SN, Chavda P, Udhani S, Shukla D, Pathak S, Ojha R (2015) A survey on incidence of common dental problems among patients attending dentistry OPD at a tertiary care hospital from central Gujarat. Int J Res MedGoogle Scholar
  26. 26.
    Harris M, Eaton KA (2011) Discussion paper, dental hyginest and dental research: a developing scene OHDM 10(4)Google Scholar
  27. 27.
    Shivpuje BV, Sable GS (2016) A review on digital dental radiographic images for disease identification and classification. Int J Eng Res Appl 6(7) (Part -5):38–42. ISSN 2248-9622Google Scholar
  28. 28.
    Melin P, Gonzalez CI, Castro JR, Mendoza O, Castillo O (2013) Edge detection method for image processing based on generalized type-2. Fuzzy Logic IEEE. Scholar
  29. 29.
    Melin P, Gonzalez CI, Castro JR, Mendoza O, Castillo O (2016) General type-2 Fuzzy edge detector applied on face recognition system using neural networks. IEEE 978-1-5090-0626-7Google Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Electronics and Communication EngineeringLovely Professional UniversityPhagwaraIndia

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