`function operator = configureCOSFIRE(prototypePattern, keypoint)`

Department of Computing Science, Intelligent Systems

This page contains an overview of the COSFIRE operator and an example concerning the corresponding Matlab scripts. With this implementation you can configure a COSFIRE filter by a given prototype pattern and apply the resulting COSFIRE filter to a given testing image for the detection of patterns that are similar to the prototype pattern.

`function operator = configureCOSFIRE(prototypePattern, keypoint)`

- Input Parameters
**prototypePattern**is an intensity image that contains a prototype pattern.**keypoint**is the pair [row,col] coordinates of the point of interest that characterizes the prototype pattern

- Output Parameter
**operator**is a structure containing two parameters, namely**tuples**and**params**. The parameter**operator.tuples**is a matrix of 4 rows and n columns, where each column of 4 values (lambda, theta, rho, phi) characterizes the properties of a contour part from the prototype pattern, The parameter**operator.params**is another structure that contains all the parameter values required by a COSFIRE filter, such as a list of radii values of a number of concentric cirlces.

```
proto = imread('pattern.bmp');
operator = configureCOSFIRE(proto,[116,132]);
viewCOSFIREstructure(operator);
```

`function output = configureCOSFIRE(testingImage, operator)`

- Input Parameters
**testingImage**is an intensity image to which we apply the given operator**operator**is a structure that represents a COSFIRE filter

- Output Parameter
**output**is the response matrix of the COSFIRE operator whose elements vary between 0 and 1.

```
I = imread('pattern.bmp');
output = applyCOSFIRE(I, operator);
```

I | output | The marked red spots illustrate the locations of the local maxima values of the COSFIRE output |

[1] G. Azzopardi and N. Petkov, "Trainable COSFIRE filters for keypoint detection and pattern recognition",

Last changed: 2012-07-01 |