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FPGA implementation of low power and high speed image edge detection algorithm

机译:低功率和高速图像边缘检测算法的FPGA实现

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Image processing is a vital task in data processing system for applications in medical fields, remote sensing, microscopic imaging etc., Algorithms for processing image exist except for real time system style, hardware implementation is most popular principally. This paper presents a design for Sobel filter based edge detection on Field Programmable Gate Array (FPGA) board. Hardware implementation of the Sobel edge detection algorithm is chosen because it presents an honest scope for similarity over software package. On the opposite hand, Sobel edge detection will work with less deterioration in high level of noise. Edges are primarily the noticeable variation of intensities in a picture. Edges facilitate to spot the placement of an object and also the boundary of a selected entity within the image. It conjointly helps in feature extraction and pattern recognition. Hence, edge detection is of nice importance in pc vision. The planned design for edge detection exploitation Sobel algorithm is designed using structural Verilog lipoprotein synthesized exploitation Cadence Genus and enforced using Cadence Innovus. The practicality of the planning is verified exploitation normal pictures by FPGA implementation. The proposed architecture reduce the power, delay and space complexity compare to three existing architectures. (C) 2020 Elsevier B.V. All rights reserved.
机译:图像处理是医疗领域的应用程序中的数据处理系统中的重要任务,遥感,微观成像等,用于处理图像的算法,除了实时系统风格,硬件实现主要是主要流行的。本文为现场可编程门阵列(FPGA)板上的Sobel过滤器的边缘检测提供了一种设计。选择了Sobel边缘检测算法的硬件实现,因为它呈现出软件包相似的诚实范围。在对方,Sobel边缘检测将在高水平的噪声中使用较少的劣化。边缘主要是图片中强度的显着变化。边缘有助于发现对象的放置以及图像内所选择的实体的边界。它在特征提取和模式识别中有助于帮助。因此,边缘检测对于PC愿景非常重要。边缘检测开发SOBEL算法的计划设计是使用结构Verilog脂蛋白合成剥削节奏属的设计,并使用Cadence Innovus实施。规划的实用性是通过FPGA实施进行验证的利用正常图片。拟议的架构将功率,延迟和空间复杂性降低到三个现有架构。 (c)2020 Elsevier B.v.保留所有权利。

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