Edge Detection with the Roberts operator Similar options are available with the

Question

Edge Detection with the Roberts operator Similar options are available with the edge function when the Roberts operator is used 8. Extract the edges from the original image using the Roberts operator. I rob1 3 edge (I, roberts figure subplot (2,2,1) imshow (I) title Orig inal Image subplot (2,2, 2) imshow (I robl) title Roberts default thresh 9. Apply the Roberts operator to a noisy image. [I rob2 t] edge (I noise roberts' subplot (2,2,3) imshow (I noise), title Image w noise subplot (2,2 imshow (I rob2), title ('Roberts on noise

Explanation / Answer

8.)Roberts:

In Robert edge detection, the vertical and horizontal edges bring out individually and then put together for resulting edge detection. The Roberts edge detector uses the following masks to approximate digitally the first derivatives as differences between adjacent pixels.

Sobel:

The sobel edge detector computes the gradient by using the discrete differences between rows and columns of a 3X3 neighborhood. The sobel operator is based on convolving the image with a small, separable, and integer valued filter. Sobel operator is discrete differential operator, computes an approximation of the gradient of the image intensity function. After applying Sobel operator, every point in the resulting image will be the corresponding gradient vector or norm of that vector. The Sobel operator is based on convolution of the image with a small, separable and integer valued filter is applied in vertical and horizontal directions which results in less computations therefore it is less expensive. And the result of gradient approximation is crude. Sobel Operator mask are:

Prewitt:

Prewitt operator edge detection masks are the one of the oldest and best understood methods of detecting edges in images The Prewitt edge detector uses the following mask to approximate digitally the first derivatives Gx and Gy. It is a discrete differentiation operator. It computes the approximation of gradient intensity function. The result of Prewitt operator is either the corresponding gradient vector or normal of this vector. It is based on the convolving the image with small, separable and integer valued filter in horizontal(x) and vertical(y) direction. It is computationally less expensive and faster method for edge detection. It is only appropriate for noiseless and well contrasted. The difference between Prewitt and Sobel operator is the spectoral response. It is an appropriate way to estimate the magnitude and orientation of an edge.

The derivatives should have the following properties:

• Mask should contain opposite signs.

• Sum of mask should be equal to zero.

• More edge detection due to more weight.

Prewitt operator generates two masks, one for detecting edges in horizontal direction and other for vertical direction.

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