edgetools (edgemap.m + edgedir.m) Matlab tools to find edges of a digital image
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- category Application
- package \Com\Tecnick\edgetools
- author Nicola Asuni info@tecnick.com
- copyright 2006-2016 Nicola Asuni - Tecnick.com LTD
- license http://www.gnu.org/copyleft/lesser.html GNU-LGPL v3 (see LICENSE.TXT)
- link https://github.com/tecnickcom/edgetools
- version 1.1.1
This function detects edges, which are those places in an image that correspond to object boundaries. To find edges, this function looks for places in the image where the intensity changes rapidly, using an improved SUSAN technique.
This algorithm is based on the technique described on: S.M. Smith, J.M. Brady, "SUSAN - a new approach to low level image processing", Int Journal of Computer Vision, 23(1):45-78, May 1997. This technicque is subject to a patent: S.M. Smith, "Method for digitally processing images to determine the position of edges and/or corners therein for guidance of unmanned vehicle. UK Patent 2272285. Proprietor: Secretary of State for Defence, UK. 15 January 1997.
[EDG] = edgemap(IM) [EDG] = edgemap(IM, TR) [EDG] = edgemap(IM, TR, KR) [EDG] = edgemap(IM, TR, KR, NR) [EDG] = edgemap(IM, TR, KR, NR, OP)
IM : source image (RGB or grayscale) TR : Brightness Threshold (default = 20) KR : USAN Kernel Radius (nucleus excluded) (default = 3) NR : EDG matrix will be normalized to this range of integers (default = 0 = not normalize) OP : if true removes from USAN the pixels that are not directly connected with the nucleus (default = false). IMPORTANT: This optimization is very slow, so use it carefully only for small images and when it's really needed.
EDG : edge strength image
Please check the edgexample.m and edgexample2.m files on how to use this function.
This implementation is not intended to be used in a production environment. The main purpose of this script is to clearly show how this technique works. Better performaces could be obtained using a compiled version or rewriting this technique using a low-level programming language.
This function detects the angles of the tangents to image edges. Angles are counted counter-clockwise starting from horizontal. The edges are those places in an image that correspond to object boundaries. To find the angles of edges, this function uses a modified SUSAN technique. % This algorithm is based on the technique described on: S.M. Smith, J.M. Brady, "SUSAN - a new approach to low level image processing", Int Journal of Computer Vision, 23(1):45-78, May 1997. This technicque is subject to a patent: S.M. Smith, "Method for digitally processing images to determine the position of edges and/or corners therein for guidance of unmanned vehicle. UK Patent 2272285. Proprietor: Secretary of State for Defence, UK. 15 January 1997.
SUSAN, image, edge, detection, detector, orientation, direction, matlab, octave.
This function is slow because of high computational complexity.
[ANG] = edgedir(EDG) [ANG] = edgedir(EDG, KR) [ANG] = edgedir(EDG, KR, OP)
EDG : edge strength image KR : USAN Kernel Radius (nucleus excluded) (default = 3) OP : if true removes from USAN the pixels that are not directly connected with the nucleus (default = false). IMPORTANT: This optimization is very slow, so use it carefully only for small images and when it's really needed.
ANG : angles of the tangents to image edges (edge orientation) in radiants ]0,pi]. Angles are counted counter-clockwise starting from horizontal.
Please check the edgexample.m and edgexample2.m files on how to use this function (uncomment the last line of these files to calculate and print the edge orientation matrix).
This implementation is not intended to be used in a production environment. The main purpose of this script is to clearly show how this technique works. Better performaces could be obtained using a compiled version or rewriting this technique using a low-level programming language.
Check the edgexample.m and edgexample2.m scripts for usage example.
