A Review of Classic Edge Detectors

Abstract

In this paper some of the classic alternatives for edge detection in digital images are studied. The main idea behind edge detection is to find where abrupt changes in the intensity of an image have occurred. The first family of algorithms reviewed in this work uses the first derivative to find the changes of intensity, such as Sobel, Prewitt and Roberts. In the second reviewed family it is used second derivative, for example in algorithms like Marr-Hildreth and Haralick. Results obtained from a qualitative point of view (perceptual) and from a quantitative point of view (number of operations, execution time) are compared, considering different ways to convolve an image with a kernel (step required in some of the algorithms).