• Corpus ID: 212467408

A Review and Research of Edge Detection Techniques for Image Segmentation

@inproceedings{Dhankhar2013ARA,
  title={A Review and Research of Edge Detection Techniques for Image Segmentation},
  author={Poonam Dhankhar and Neha Sahu},
  year={2013}
}
Interpretation of image contents is one o f the main objectives in computer vision. The purpo se of Image segmentation is to partition an image into me aningful regions with respect to a particular appli cation. Image segmentation is a method of separating the im age from the background and read the contents. Edge is a basic and important feature of an image. Image is a combination of edges. Detecting edges is one of the most important aspects in image segmentation. Edge etection is a vital… 
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32 Citations
Highly Influential Citations
2
Background Citations
5
Methods Citations
8
Results Citations
1

32 Citations

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Citation Type

Image Segmentation of Color Image using Threshold Based Edge Detection Algorithm in MatLab
TLDR
A new edge detection technique is proposed which detects the acute and precise edges that are not possible with the pre-existing techniques, and can be improved by combining it with other types of filters namely STD, Weiner, Harmonic, Geometric filters to eliminate the noise from the image.
Survey on Various Edge Detection Techniques on Noisy Images
TLDR
A clear-cut explanation of various edge detection algorithms with comparison on image with salt and pepper noise and preprocessed images and on comparing them the authors can say that image filtered by median filter gives better output than noisy image.
Analytical Comparison between Sobel and Prewitt Edge Detection Techniques
TLDR
Two edge detection techniques, Sobel edge detection and Prewitt edge detection technique, are used to extract edges from the images of flowers and from experimental results, it is observed that the P Drewitt edge Detection technique works better as compared to Sobel edges detection technique.
A Review on Edge Detection Techniques for Image Segmentation
TLDR
From the results, Canny Optimal Edge detection (COE) technique provides identifies the edges effectively for noisy and complex images when compared to other techniques.
Role of Image Segmentation in Digital Image Processing for Information Processing
Digital Image processing is a technique using computer algorithms to perform specific operations on an image, in order to get an enhanced image or to extract some useful information from it. Image…
Morphological based segmentation of brain image for tumor detection
TLDR
The brain image is considered for analysis and detection of bio-medical image contents and the result obtained using Gaussian filter shows better performance than other methods.
A COMPARATIVE ANALYSIS OF EDGE DETECTION TECHNIQUES USED IN FLAME IMAGE PROCESSING
TLDR
The study has been done on various edge detection methods such as Sobel, Robert’s cross, Prewitt, Laplacian of Gaussian, Canny edge detection & the technique which is based on Local Binary Pattern (LBP).
Improvement In Watershed Image Segmentation For High Definition Images
TLDR
This paper aims to resolve the problem of over-segmentation by reducing the size of the image first and then reducing the noise of the reduced size image and comparing the PSNR value of the traditional watershed algorithm to the improved watershed algorithm.
Enhancing the Process to Detect Edges using PIYA
TLDR
In this paper, edge detection algorithm PIYA was studied and results with the available conventional edge detectors as SOBEL, PRIWITT, ROBERTS are compared.
Global Canny algorithm based on Canny edge detector framework in magnetic resonance imaging
TLDR
The result shows that the proposed method can yield better edge detection than conventional method, with minimal false edge detection, and undergoes several attempts of parameter adjustment to detect true edges successfully using optimal parameter setting.
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References

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TLDR
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Image Segmentation using Edge Detection and Threshold ”
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  • 2012
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