Proceedings ArticleDOI
Medical Images Edge Detection Based on Mathematical Morphology
Zhao Yu-qian,Gui Wei-hua,Chen Zhen-cheng,Tang Jing-tian,Li Ling-yun +4 more
- Vol. 2005, pp 6492-6495
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TLDR
A novel mathematical morphological edge detection algorithm is proposed to detect the edge of lungs CT image with salt-and-pepper noise and the experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used template-based edge detection algorithms and general morphologicalEdge detection algorithms.Abstract:
Medical images edge detection is an important work for object recognition of the human organs and it is an important pre-processing step in medical image segmentation and 3D reconstruction. Conventionally, edge is detected according to some early brought forward algorithms such as gradient-based algorithm and template-based algorithm, but they are not so good for noise medical image edge detection. In this paper, basic mathematical morphological theory and operations are introduced at first, and then a novel mathematical morphological edge detection algorithm is proposed to detect the edge of lungs CT image with salt-and-pepper noise. The experimental results show that the proposed algorithm is more efficient for medical image denoising and edge detection than the usually used template-based edge detection algorithms and general morphological edge detection algorithmsread more
Citations
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Book ChapterDOI
Edge Detection of Flat Electroencephalography Image via Classical and Fuzzy Approach
TL;DR: The boundary of the epileptic foci of Flat EEG (fEEG) is determined by implementing some of the methods ranging from classical to fuzzy approach, including Minimum Constructor and Maximum Constructor methods.
Journal Article
Subjective Evaluation of Mathematical Morphology Edge Detection on Computed Tomography (CT) Images
TL;DR: Three methods of edge detection based on mathematical morphology algorithm were applied on two sets of CT images and results show these methods are more efficient and suitable for medical image which can be used for different other applications.
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Satellite images edge detection based on morphology models fusion
TL;DR: In this method, edge detected by morphology's operator and their combination and with the use of various structure elements of images in satellite and remote sensing.
Proceedings ArticleDOI
Detail preservation of morphological operations through image scaling
TL;DR: An image scaling method is proposed that will preserve detailed information when applying morphological operations to remove noise and demonstrate the effectiveness of the proposed method in preserving the structural details such as edges while eliminating noises.
Proceedings ArticleDOI
An optimization method for edge-detector parameter tuning based on visual perception
TL;DR: An optimization method for tuning the parameters of edge detection algorithms based on visual perception is proposed and applied to the Sobel, Laplacian of Gaussian, and Canny detectors and iteratively reduces the parameter search space by means of a coordinate search.
References
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Book
Image Analysis and Mathematical Morphology
TL;DR: This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.
Journal ArticleDOI
Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks
A. Huertas,Gerard Medioni +1 more
TL;DR: A system that takes a gray level image as input, locates edges with subpixel accuracy, and links them into lines and notes that the zero-crossings obtained from the full resolution image using a space constant ¿ for the Gaussian, are very similar, but the processing times are very different.
Journal ArticleDOI
Morphologic edge detection
TL;DR: The blur-minimum morphologic edge operator is defined, its inherent noise sensitivity is less than the dilation or the erosion residue operators, and it is less computationally complex than the facet edge operator.
Journal ArticleDOI
A new algorithm for image noise reduction using mathematical morphology
TL;DR: The paper describes the MIC algorithm in detail, discusses the effects of parametric variations, presents the results of a noise analysis and shows a number of examples of its use, including the removal of scanner noise.
Journal ArticleDOI
Differential morphology and image processing
TL;DR: The analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms are viewed as a unified area in nonlinear image processing, which is called differential morphology, and its potential applications to image processing and computer vision are discussed.