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Journal of Cybersecurity and Information Management
Volume 6 , Issue 1, PP: 51-64 , 2021 | Cite this article as | XML | Html |PDF

Title

Explaining feature detection Mechanisms: A Survey

  Ahmed A. Elngar 1 * ,   Mohamed Arafa 2 ,   Mustafa Marouf 3 ,   Mahmoud Ahmed 4 ,   Nehal Fawzy 5

1  Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef City, 62511, Egypt
    (elngar_7@yahoo.co.uk)

2  Teaching assistant, Department of Computer Science, Scientific Innovation Research Group (SIRG) member, Beni-Suef University of Computers and Artificial Intelligence, Egypt
    (jenuiman4rt@gmail.com)

3  Under Graduated Student, Department of Computer Science, Scientific Innovation Research Group (SIRG) member, Beni-Suef University of Computers and Artificial Intelligence, Egypt
    (mustafa.elhersh2@gmail.com)

4  Under Graduated Student, Department of Computer Science, Scientific Innovation Research Group (SIRG) member, Beni-Suef University of Computers and Artificial Intelligence, Egypt
    (ma7mouda7med2251999@gmail.com)

5  Department of Electronics and Communications Engineering, Faculty of Engineering, Mansoura University, Mansoura 35516, Egypt,
    (Neehal.fawzy91@yahoo.com)

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Doi   :   https://doi.org/10.54216/JCIM.060103

Received: November 24, 2020 Revised: February 9, 2021 Accepted: March 15, 2021

Abstract :

 

Feature detection, description and matching are essential components of various computer vision applications; thus, they have received a considerable attention in the last decades. Several feature detectors and descriptors have been proposed in the literature with a variety of deļ¬nitions for what kind of points in an image is potentially interesting (i.e., a distinctive attribute). This chapter introduces basic notation and mathematical concepts for detecting and describing image features. Then, it discusses properties of perfect features and gives an overview of various existing detection and description methods. Furthermore, it explains some approaches to feature matching. Finally, the chapter discusses the most used techniques for performance evaluation of detection algorithms.

 

Keywords :

Interest points , Feature detector , Feature descriptor , Feature extraction , Feature matching

References :

[1]   T. Lindeberg (2008–2009). "Scale-space". In Benjamin Wah (ed.). Encyclopedia of Computer Science and Engineering. IV. John Wiley and Sons. pp. 2495–2504. doi:10.1002/9780470050118.ecse609. ISBN 978-0470050118. (summary and review of a number of feature detectors formulated based on a scale-space operations)

[2]   Canny, J. (1986). "A Computational Approach To Edge Detection". IEEE Transactions on Pattern Analysis and Machine Intelligence. 8 (6): 679–714. doi:10.1109/TPAMI.1986.4767851. (Canny edge detection)

[3]   C. Harris; M. Stephens (1988). "A combined corner and edge detector" (PDF). Proceedings of the 4th Alvey Vision Conference. pp. 147–151.(Harris/Plessey corner detection)

[4]   S. M. Smith; J. M. Brady (May 1997). "SUSAN - a new approach to low level image processing". International Journal of Computer Vision. 23 (1): 45–78. doi:10.1023/A:1007963824710.(The SUSAN corner detector)

[5]   J. Shi; C. Tomasi (June 1994). "Good Features to Track,". 9th IEEE Conference on Computer Vision and Pattern Recognition. Springer.(The Shi and Tomasi corner detector)

[6]   E. Rosten; T. Drummond (2006). "Machine learning for high-speed corner detection". European Conference on Computer Vision. Springer. pp. 430–443. CiteSeerX 10.1.1.60.3991. doi:10.1007/11744023_34.(The FAST corner detector)

[7]   T. Lindeberg (1998). "Feature detection with automatic scale selection" (abstract). International Journal of Computer Vision. 30 (2): 77–116. doi:10.1023/A:1008045108935.(Laplacian and determinant of Hessian blob detection as well as automatic scale selection)

[8]   D. Lowe (2004). "Distinctive Image Features from Scale-Invariant Keypoints". International Journal of Computer Vision. 60 (2): 91. CiteSeerX 10.1.1.73.2924. doi:10.1023/B:VISI.0000029664.99615.94.(DOG blob detection with automatic scale selection)

[9]   J. Matas; O. Chum; M. Urban; T. Pajdla (2002). "Robust wide baseline stereo from maximally stable extremum regions" (PDF). British Machine Vision Conference. pp. 384–393.(The MSER blob detector)

[10] T. Lindeberg (1993). "Detecting Salient Blob-Like Image Structures and Their Scales with a Scale-Space Primal Sketch: A Method for Focus-of-Attention" (abstract). International Journal of Computer Vision. 11 (3): 283–318. doi:10.1007/BF01469346.(Grey-level blob detection and scale-space blobs)

[11] R. Haralick, "Ridges and Valleys on Digital Images," Computer Vision, Graphics, and Image Processing vol. 22, no. 10, pp. 28–38, Apr. 1983. (Ridge detection using facet model)

[12] J. L. Crowley and A. C. Parker, "A Representation for Shape Based on Peaks and Ridges in the Difference of Low Pass Transform", IEEE Transactions on PAMI, PAMI 6 (2), pp. 156–170, March 1984. (Ridge detection based on DOGs)

[13] D. Eberly, R. Gardner, B. Morse, S. Pizer, C. Scharlach, Ridges for image analysis, Journal of Mathematical Imaging and Vision, v. 4 n. 4, pp. 353–373, Dec. 1994. (Fixed scale ridge detection)

[14] T. Lindeberg (1998). "Edge detection and ridge detection with automatic scale selection" (abstract). International Journal of Computer Vision. 30 (2): 117–154. doi:10.1023/A:1008097225773.(Ridge detection with automatic scale selection)

[15] T. Lindeberg (2008–2009). "Scale-space". In Benjamin Wah (ed.). Encyclopedia of Computer Science and Engineering. IV. John Wiley and Sons. pp. 2495–2504. doi:10.1002/9780470050118.ecse609. ISBN 978-0470050118. (summary and review of a number of feature detectors formulated based on a scale-space operations)

[16] Canny, J. (1986). "A Computational Approach To Edge Detection". IEEE Transactions on Pattern Analysis and Machine Intelligence. 8 (6): 679–714. doi:10.1109/TPAMI.1986.4767851.. (Canny edge detection)

[17] C. Harris; M. Stephens (1988). "A combined corner and edge detector" (PDF). Proceedings of the 4th Alvey Vision Conference. pp. 147–151.(Harris/Plessey corner detection)

[18] S. M. Smith; J. M. Brady (May 1997). "SUSAN - a new approach to low level image processing". International Journal of Computer Vision. 23 (1): 45–78. doi:10.1023/A:1007963824710.(The SUSAN corner detector)

[19] J. Shi; C. Tomasi (June 1994). "Good Features to Track,". 9th IEEE Conference on Computer Vision and Pattern Recognition. Springer.(The Shi and Tomasi corner detector)

[20] E. Rosten; T. Drummond (2006). "Machine learning for high-speed corner detection". European Conference on Computer Vision. Springer. pp. 430–443. CiteSeerX 10.1.1.60.3991. doi:10.1007/11744023_34.(The FAST corner detector)

[21] T. Lindeberg (1998). "Feature detection with automatic scale selection" (abstract). International Journal of Computer Vision. 30 (2): 77–116. doi:10.1023/A:1008045108935.(Laplacian and determinant of Hessian blob detection as well as automatic scale selection)

[22] D. Lowe (2004). "Distinctive Image Features from Scale-Invariant Keypoints". International Journal of Computer Vision. 60 (2): 91. CiteSeerX 10.1.1.73.2924. doi:10.1023/B:VISI.0000029664.99615.94.(DOG blob detection 

 

 

 

Cite this Article as :
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MLA Ahmed A. Elngar, Mohamed Arafa, Mustafa Marouf, Mahmoud Ahmed, Nehal Fawzy. "Explaining feature detection Mechanisms: A Survey." Journal of Cybersecurity and Information Management, Vol. 6, No. 1, 2021 ,PP. 51-64 (Doi   :  https://doi.org/10.54216/JCIM.060103)
APA Ahmed A. Elngar, Mohamed Arafa, Mustafa Marouf, Mahmoud Ahmed, Nehal Fawzy. (2021). Explaining feature detection Mechanisms: A Survey. Journal of Journal of Cybersecurity and Information Management, 6 ( 1 ), 51-64 (Doi   :  https://doi.org/10.54216/JCIM.060103)
Chicago Ahmed A. Elngar, Mohamed Arafa, Mustafa Marouf, Mahmoud Ahmed, Nehal Fawzy. "Explaining feature detection Mechanisms: A Survey." Journal of Journal of Cybersecurity and Information Management, 6 no. 1 (2021): 51-64 (Doi   :  https://doi.org/10.54216/JCIM.060103)
Harvard Ahmed A. Elngar, Mohamed Arafa, Mustafa Marouf, Mahmoud Ahmed, Nehal Fawzy. (2021). Explaining feature detection Mechanisms: A Survey. Journal of Journal of Cybersecurity and Information Management, 6 ( 1 ), 51-64 (Doi   :  https://doi.org/10.54216/JCIM.060103)
Vancouver Ahmed A. Elngar, Mohamed Arafa, Mustafa Marouf, Mahmoud Ahmed, Nehal Fawzy. Explaining feature detection Mechanisms: A Survey. Journal of Journal of Cybersecurity and Information Management, (2021); 6 ( 1 ): 51-64 (Doi   :  https://doi.org/10.54216/JCIM.060103)
IEEE Ahmed A. Elngar, Mohamed Arafa, Mustafa Marouf, Mahmoud Ahmed, Nehal Fawzy, Explaining feature detection Mechanisms: A Survey, Journal of Journal of Cybersecurity and Information Management, Vol. 6 , No. 1 , (2021) : 51-64 (Doi   :  https://doi.org/10.54216/JCIM.060103)
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