Functions

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Component Name:
Author:
Kirsch edge map
M. Makridis (makridis@iti.gr)
Language:
C/C++
Prerequisites:
- OpenCV 2.1 or higher (latest 2.3.1) - http://opencv.willowgarage.com/wiki/
Description: This component contains a function required for calculating Kirsch edge
strength map
Ref: R. Kirsch, “Computer determination of the constituent structure of biological images,”
Computers and Biomedical Research, vol. 4, pp. 315–328, 1971
Functions
vector<vector<int>> ApplyKirsch: This function calculates
Kirsch edge strength map
Input parameters:
vector<vector<int>> SrcData:
int Bckgr: Background color. In cases of sherd classification (the
reason of Kirsch implementation) a background value is needed in
order to discard background pixels from calculations. In case of
other problem background can be set to a random negative value
(disarm it).
int bh: Image height
int bw: Image width
Output parameter:
vector<vector<int>>: A 2D vector in the size of the corresponding
image. The vector contains edge strength values normilized from 0
(dark - strong) to 255 (white - weak).
Theory
Kirsch edge map: Kirsch edge map has the dimensions of the sherd and each pixel value
corresponds to the edge strength of the pixel. Similarly to contrast feature, kirsch edge map
can lead to misclassification in non-uniformly textured images. Kirsch edge detection
algorithm implementation is summarized in the next paragraph.
Kirsch edge detection is based on image filtering with eight masks. Kirsch masks detect
edges in horizontal and vertical directions, 45, 135, 225 and 315 degrees angles. Kirsch eight
masks are defined as follows:
−3 −3 3
[−3 0 −3] ,
5
5
5
−3 −3 3
[5
0 −3] ,
5
5 −3
5
[5
5
−3 3
0 −3] ,
−3 −3
5
5
3
[5
0 −3] ,
−3 −3 −3
(1)
5
5
5
[−3 0 −3] ,
−3 −3 −3
−3 5
5
[−3 0
5 ],
−3 −3 −3
−3 −3 5
[−3 0 5] ,
−3 −3 5
−3 −3
[−3 0
−3 5
−3
5]
5
For each pixel of the sherd image the largest absolute value is considered as pixel’s edge
value. In the following figure, an example of Kirsch edge map is illustrated.
(a)
(b)
Kirsch edge map for a single sherd view
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