Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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One of the challenging topics in image processing is extracting the shapes from noisy backgrounds. There are some methods for doing it from different kinds of noisy backgrounds. In this paper, we are going to introduce another method by using 4 steps to extract circular shapes from impulse noisy backgrounds. First step is applying median filter to disappear “salt and pepper” noise. This step causes edge smoothing. So, as the second step, a laplacian sharpening spatial filter should be applied. It highlights fine details and enhances the blurred edges. Using these two steps sequentially causes noise reduction in an impressive way. Third step is using Canny edge detection for segmenting the image. Its algorithm is talked during the paper. Finally, forth step is applying Circular Hough Transform (CHT) for detecting the circles in image. At the end of paper different use cases of this method is investigated.
Masoud Nosrati. 1970. \u201cDetecting circular shapes from areal images using median filter and CHT\u201d. Unknown Journal GJCST Volume 12 (GJCST Volume 12 Issue 2): .
The methods for personal identification and authentication are no exception.
Total Score: 88
Country: Iran
Subject: Uncategorized
Authors: Dr. Masoud Nosrati,Ronak Karimi,Mehdi Hariri (PhD/Dr. count: 1)
View Count (all-time): 109
Total Views (Real + Logic): 20608
Total Downloads (simulated): 10825
Publish Date: 1970 01, Thu
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Neural Networks and Rules-based Systems used to Find Rational and
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One of the challenging topics in image processing is extracting the shapes from noisy backgrounds. There are some methods for doing it from different kinds of noisy backgrounds. In this paper, we are going to introduce another method by using 4 steps to extract circular shapes from impulse noisy backgrounds. First step is applying median filter to disappear “salt and pepper” noise. This step causes edge smoothing. So, as the second step, a laplacian sharpening spatial filter should be applied. It highlights fine details and enhances the blurred edges. Using these two steps sequentially causes noise reduction in an impressive way. Third step is using Canny edge detection for segmenting the image. Its algorithm is talked during the paper. Finally, forth step is applying Circular Hough Transform (CHT) for detecting the circles in image. At the end of paper different use cases of this method is investigated.
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