NDLI: Segmentation of digital images with various edge detection techniques using OpenCV

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Segmentation of digital images with various edge detection techniques using OpenCV

Content Provider	Scilit
Author	Shukla, Saumitra Kikan, Vaishali Sachdeva, Ritvi Chaturvedi, Yash Jain, Ronak
Copyright Year	2021
Description	In the domain of computer vision or image segmentation, Edge detection is the most widely used technique to determine and outline the presence of lines or objects in an image appropriately. The main aim is to segment the image data so that the complexity of the image is reduced also the amount of data to be processed in further steps of advanced algorithm is reduced. In simple language, we can say that edges are the sudden and significant changes in the intensity of the image which occur at the boundary of an object in the image. In this paper, the Sobel operator technique, the Laplacian technique, and the Canny technique are used and compared with one another for edge detection in an image. This paper represents the detailed analysis of the performance of these edge detection tools by using the input images with different types of backgrounds for the computer vision or image segmentation or any other advanced algorithm. Further, we have done the comparison among these techniques in presence of different types of noise by using the OpenCV library and PythonSoftware. Book Name: Recent Trends in Communication and Electronics
Related Links	https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781003193838-99&type=chapterpdf
Ending Page	539
Page Count	5
Starting Page	535
DOI	10.1201/9781003193838-99
Language	English
Publisher	Informa UK Limited
Publisher Date	2021-06-19
Access Restriction	Open
Subject Keyword	Book Name: Recent Trends in Communication and Electronics Hardware and Architecturee Edge Detection Computer Vision Or Image Segmentation
Content Type	Text
Resource Type	Chapter

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