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6 articles for “canny edge detection method”
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Detect the Edges in Satellite Image Using CED Algorithm
Abstract: Edge detection is that the name for a collection of mathematical strategies that aim at distinguishing points in a very digital image at that the image brightness changes sharply or, a lot of formally, has discontinuities. The points at that image brightness changes sharply square measure generally organized into a collection of flexuous line segments termed edges. Constant drawback of finding discontinuities in 1D signal is understood as step and …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 3, 2015 · pp. 30–35 Read article
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Driver Drowsiness Detection Using Canny Edge Detection and Hough Transformation
Abstract: AbstractThe aim of this study is to save many lives during road accidents because of driver’s drowsiness. A method for detecting sleepiness in drivers is developed by using a camera that points directly towards the driver’s face and captures the video. Once a video is captured, it detects a face and continues monitoring the face region and eyes in order to detect fatigue. Viola Jones algorithm is used to detect …
Published in Journal of Open Source Developments · Vol. 4, Issue 3, 2017 · pp. 9–13 Read article
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A Novel Blind Restoration Technique Using Different Edge Detection Methods
Abstract: Image restoration is a field of image processing in which we recover an original image from a degraded image. Objective of this paper is to compare different blurred and noisy images which are reconstructed with the help of blind deconvolution algorithm using different edge detection methods such as Canny, Sobel, Prewitt, Roberts, Laplacian. Initially original image is blurred using Gaussian filter. After that in the edges of blurred image ringing …
Published in Journal of Operating Systems Development & Trends · Vol. 1, Issue 2, 2014 · pp. 1–5 Read article
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Image Super Resolution Using Back-Projection based on Canny Edge Detection and Gabor Filter Prior
Abstract: In recent years, due to the advancement of mixed media instrumentation and machine gadgets, single-image super resolution has currently been converted into a thought subject. Super-resolution is the procedure of improving a high-resolution image from varied low-resolution pictures of a similar scene. The key goal of super-resolution imaging is to reproduce a higher-resolution image focused around a group of pictures, procured from a similar scene and indicated as “low-resolution” pictures, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 3, 2015 · pp. 48–56 Read article
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Analogy between Various Edge Detection Algorithms
Abstract: Image segmentation is the technique of detecting edges of the object within the picture that we want to identify. Image recognition is carried out in various steps: Step 1: RGB value of picture is extracted. Step 2: Gray image is acquired either using formulae 0.2989×R+0.5870×G+0.1140×B or the usage of rgb2gray() function. Step 3: Binary image is acquired from gray image. Step 4: Now edge detection is implemented using various algorithms …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 39–44 Read article
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Optical Image Sensing and Analysis of Iron Ore Pellets: A Machine Learning Approach
Abstract: The present work is aimed to improve quality control in steel production using SEM imaging and machine learning. High-resolution SEM images of iron ore pellets, primarily composed of hematite and magnetite, are analyzed to understand their microstructural features, which significantly impact pellet performance during reduction processes. Traditional microstructure analysis is manual, time- consuming, and prone to inconsistencies. This study proposes an automated approach using K-Means Clustering, Canny Edge Detection, DBSCAN, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 7–18 Read article