Conclusion#

We have seen in that chapter that methods for finding features are very different and depend on the seeking feature.

  • For edges, usual methods are essentially a filtering using the gradient or the Laplacian (Roberts or Prewitt filters, Sobel or Canny detectors).

  • For corners, the dedicated methods analyze the variation in intensity in the neighbourhood of the pixels (Moravec and Harris detectors).

  • For lines and circles, the image is represented in the space of the parameters of the geometric shape (Hough transform).

References#

  • J. Canny, “A Computational Approach To Edge Detection”, IEEE Transactions on Pattern Analysis and Machine Intelligence}, vol.8, 1986.

  • C. Harris and M. Stephens “A combined corner and edge detector”, Alvey Vision Conference, p. 147-151, 1988.

  • P.V.C. Hough, “Method and means for recognizing complex patterns”, US Patent 3,069,654, 1962.

  • D. Marr and E. Hildreth, “Theory of Edge Detection”, Proceedings of the Royal Society of London, vol. 207, 1980.

  • H. Moravec, “Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover”, technical report, Carnegie–Mellon University, Robotics Institute, 1980.

  • J.M.S. Prewitt, “Object enhancement and extraction”, Picture Processing and Psychopictorics, Academic Press, 1970.

  • L.G. Roberts, “Machine Perception Of Three-Dimensional Solids”, Computer Methods in Image Analysis, IEEE Press, 1965.

  • I. Sobel and G. Feldman, “A \(3\times3\) Isotropic Gradient Operator for Image Processing”, In Stanford Artificial Intelligence Project, 1968.