Advances of Soft Computing Methods in Edge Detection

Artificial Intelligence (AI) techniques are now commonly used to solve complex and ill-defined problems. AI a broad field and will bring different meanings for different people. John McCarthy would probably use AI as “computational intelligence”, while Zadeh claimed that computational intelligence is actually Soft Computing (SC) techniques. Regardless of its definition, AI concerns with tasks that require human intelligence which require complex and advanced reasoning processes and knowledge. Due to its ability to learn, handle incomplete or incomprehensible data, deal with nonlinear problems, and perform reasonable tasks very fast, AI has been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social sciences. However, in this paper, we will focus on Soft Computing (SC), one of the AI influences that sprang from the concept of cybernetics. The main objective of this paper is to illustrate how some of these SC techniques generally work on detecting the edges. The paper also outlines practical differences among these techniques when they are applied to solving the problem of edge detection