*2.3. Prewitt's Operator*

Prewitt operator is a method of selecting boundaries in image processing, which calculates the maximum response on the set of convolution cores to find the local orientation of the border in each pixel. It was created by Dr. Judith Prewitt to identify the boundaries of medical imaging [31].

Different kernels are used for this operation. From one core, you can obtain eight, rearranging the coefficients in a circle. Each result will be sensitive to the direction of the limit from 0 to 315 with a step of 45, where 0 corresponds to the vertical limit. The maximum response of each pixel is the value of the corresponding pixel in the original image. Its values are between 1 and 8, depending on the number of nuclei that provide the greatest result.

This method of edge detection is also called edge template matching because the image is mapped to a set of templates, and each represents some boundary orientation. The size and orientation of the border in a pixel is then determined by the pattern that best matches the local neighborhood of the pixel.

While a differential gradient detector requires a time-consuming calculation of the orientation estimate for magnitudes in the vertical and horizontal directions, the Prewitt limit detector provides a direct direction from the nucleus with maximum result. The set of nuclei is limited to 8 possible directions, but experience shows that most direct estimates of orientation are also not very accurate. On the other hand, a set of cores requires 8 convolutions for each pixel, while a set of gradients of the gradient method requires only 2: sensitive vertically and horizontally.
