The IUP Journal of Telecommunications
State-of-the-Art Image Edge Detection Techniques

Article Details
Pub. Date : Nov, 2018
Product Name : The IUP Journal of Telecommunications
Product Type : Article
Product Code : IJTC51811
Author Name : Lalit Sharma and Pawan Kumar Dahiya
Availability : YES
Subject/Domain : Telecommunications
Download Format : PDF Format
No. of Pages : 11



The detection of edge inside the image is a fundamental process in digital image processing. In the computer vision and machine vision field, edge detection is used for image segmentation and data or feature extraction. The common methods for edge detection include Sobel, Canny, Prewitt, Roberts, etc. These methods are mainly implemented on the software and hence these are slower. To increase the speed of processing and give results in real time, a dedicated hardware implementation is required. For this, Field Programmable Gate Array (FPGA) is a suitable platform. The paper presents various FPGA-based implementation of image edge detection techniques and their comparison with the software-based implementation.


In the field of image segmentation, texture feature extraction, target area identification and other regional forms of edge detection in image processing play a key role. Basically, edge detection is used to get the boundaries of the objects present in image. The most widely used operators for edge detection are Sobel, Canny, Prewitt, Roberts and Fuzzy Logic (Lakshmi and Sankaranarayanan, 2010). Many applications such as military-based drones and autonomous vehicles require results on the real-time basis and thus processing capability is a major concern in the implementation of these image processing applications, which include the processing of large-size image or video.


Field Programmable Gate Array (FPGA), Edge detection, Smoothing filter,Gradient

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