Advances of Soft Computing Methods in Edge Detection
Advances of Soft Computing Methods in Edge Detection
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发表时间：
2009-11
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通讯作者：
Amir Atapour-Abarghouei;A. Ghanizadeh;S. Shamsuddin
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作者：
Amir Atapour-Abarghouei;A. Ghanizadeh;S. Shamsuddin
人工智能（AI）技术现在通常用于解决复杂和不明确的问题。人工智能是一个广阔的领域，对不同的人会带来不同的意义。约翰·麦卡锡可能会把人工智能称为“计算智能”，而扎德则声称计算智能实际上是软计算（SC）技术。无论其定义如何，人工智能关注的是需要人类智能的任务，这些任务需要复杂而先进的推理过程和知识。由于人工智能具有学习、处理不完整或不可理解的数据、处理非线性问题和快速执行合理任务的能力，人工智能在控制、机器人、模式识别、预测、医学、电力系统、制造、优化、信号处理和社会科学等领域得到了广泛的应用。然而，在本文中，我们将重点关注软计算（SC），这是人工智能的影响之一，源于控制论的概念。本文的主要目的是说明这些SC技术一般是如何检测边缘的。本文还概述了这些技术在解决边缘检测问题时的实际差异。
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.