基于知识邻域规则驱动的边缘检测方法

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY International Journal of Engineering and Technology Innovation Pub Date : 2023-01-01 DOI:10.46604/ijeti.2023.9710
Yavuz Çapkan, H. Altun, C. Fidan
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引用次数: 1

摘要

边缘检测是一个基本过程,因此仍然需要提高其效率和计算复杂性。本研究提出了一种基于知识的边缘检测方法,通过引入一组基于知识的规则来满足这一要求。导出规则的方法基于观察到的边缘像素的连续性特性和邻域特性,这些特性被表示为简单的算术运算,以提高计算复杂性。结果表明,该方法在性能和计算量方面优于基于梯度的方法。它比Canny方法快四倍,并且与一般基于梯度的方法相比显示出优越的性能。此外,所提出的方法提供了鲁棒性,可以有效地识别拐角处的边缘。由于其计算量小和固有的并行性,该方法也适用于现场可编程门阵列(FPGA)的硬件实现。
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Edge Detection Method Driven by Knowledge-Based Neighborhood Rules
Edge detection is a fundamental process, and therefore there are still demands to improve its efficiency and computational complexity. This study proposes a knowledge-based edge detection method to meet this requirement by introducing a set of knowledge-based rules. The methodology to derive the rules is based on the observed continuity properties and the neighborhood characteristics of the edge pixels, which are expressed as simple arithmetical operations to improve computational complexity. The results show that the method has an advantage over the gradient-based methods in terms of performance and computational load. It is appropriately four times faster than Canny method and shows superior performance compared to the gradient-based methods in general. Furthermore, the proposed method provides robustness to effectively identify edges at the corners. Due to its light computational requirement and inherent parallelization properties, the method would be also suitable for hardware implementation on field-programmable gate arrays (FPGA).
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来源期刊
CiteScore
2.80
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The IJETI journal focus on the field of engineering and technology Innovation. And it publishes original papers including but not limited to the following fields: Automation Engineering Civil Engineering Control Engineering Electric Engineering Electronic Engineering Green Technology Information Engineering Mechanical Engineering Material Engineering Mechatronics and Robotics Engineering Nanotechnology Optic Engineering Sport Science and Technology Innovation Management Other Engineering and Technology Related Topics.
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