NDLI: Investigation on the effect of a Gaussian Blur in image filtering and segmentation

Content Provider	IEEE Xplore Digital Library
Author	Gedraite, E.S. Hadad, M.
Copyright Year	2011
Description	Author affiliation: Students at University of São Paulo, Av. Luciano Gualberto, travessa 3, n° 380, Brazil (Gedraite, E.S.; Hadad, M.)
Abstract	The present work investigates the qualitative and quantitative effects of the convolution of a Gaussian function with an image. Besides the evaluation of the commonly called "Gaussian-blur" in the filtering of images, this work also investigates a methodology of segmentation using Gaussian blurring. Noise is inherent to the physical process of acquisition. Therefore, to know the effects of a filtering technique it is fundamental to choose the right technique to filter the image properly, since the segmentation process could be very expensive and time-consuming. An automated method for segmentation that saves time and human labor is always desirable. To evaluate the filtering characteristics, we chose a Quality Index in order to analyze in a quantitative way the effects of the convolution. Results show that the Gaussian Blur technique is to be used in images with high noise and with a Gaussian function of small variance whereas larger variance Gaussian function is more relevant in segmentation of images.
Starting Page	393
Ending Page	396
File Size	293065
Page Count	4
File Format	PDF
ISBN	9781612849492
ISSN	13342630
e-ISBN	9789537044121
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-14
Publisher Place	Croatia
Access Restriction	Subscribed
Rights Holder	ELMAR (Electronics in Marines)
Subject Keyword	Image segmentation Filtering Convolution Segmentation Liver Gaussian Blur Kernel Signal to noise ratio
Content Type	Text
Resource Type	Article

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