Edge Detection Using Matlab

Edge Detection of Image Using MATLAB

There are many operators in MATLAB for finding images

1. Sobers Operator

2. Roberts Operator

3. Prewitts Operator

4. Laplacian of Gaussian Method

5. Zero-Cross Method, etc..

To use them in MATLAB there is a function called as edge(I).

Syntax :

BW = edge(I)

BW = edge(I,'sobel')

BW = edge(I,'prewitt')

BW = edge(I,'roberts') etc.

Description :

BW = edge(I) takes a grayscale or a binary image I as its input, and returns a binary image BWof the same size as I, with 1's where the function finds edges in I and 0's elsewhere.

By default, edge uses the Sobel method to detect edges but the following provides a complete list of all the edge-finding methods supported by this function:

* The Sobel method finds edges using the Sobel approximation to the derivative. It returns edges at those points where the gradient of I is maximum.

* The Prewitt method finds edges using the Prewitt approximation to the derivative. It returns edges at those points where the gradient of I is maximum.

* The Roberts method finds edges using the Roberts approximation to the derivative. It returns edges at those points where the gradient of I is maximum.

* The Laplacian of Gaussian method finds edges by looking for zero crossings after filtering I with a Laplacian of Gaussian filter.

* The zero-cross method finds edges by looking for zero crossings after filtering I with a filter you specify.

* The Canny method finds edges by looking for local maxima of the gradient of I. The gradient is calculated using the derivative of a Gaussian filter. The method uses two thresholds, to detect strong and weak edges, and includes the weak edges in the output only if they are connected to strong edges. This method is therefore less likely than the others to be fooled by noise, and more likely...