Improved X-ray Edge Detection Based on Background Extraction Algorithm

2013 ◽  
pp. 309-319 ◽  
Author(s):  
Jakub Romanowski ◽  
Tomasz Nowak ◽  
Patryk Najgebauer ◽  
Sławomir Litwiński
Keyword(s):  
Edge Detection ◽  
X Ray ◽  
Extraction Algorithm ◽  
Background Extraction

scholarly journals Enhancing Ant-Based Algorithms for Medical Image Edge Detection by Admissible Perturbations of Demicontractive Mappings

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 885
Author(s):  
Vasile Berinde ◽  
Cristina Ţicală
Keyword(s):  
Edge Detection ◽  
Medical Image ◽  
Test Functions ◽  
Head Ct ◽  
X Ray ◽  
Numerical Tests ◽  
Image Edge Detection ◽  
Evaluation Of Parameters ◽  
Image Edge ◽  
Demicontractive Mappings

The aim of this paper is to show analytically and empirically how ant-based algorithms for medical image edge detection can be enhanced by using an admissible perturbation of demicontractive operators. We thus complement the results reported in a recent paper by the second author and her collaborators, where they used admissible perturbations of demicontractive mappings as test functions. To illustrate this fact, we first consider some typical properties of demicontractive mappings and of their admissible perturbations and then present some appropriate numerical tests to illustrate the improvement brought by the admissible perturbations of demicontractive mappings when they are taken as test functions in ant-based algorithms for medical image edge detection. The edge detection process reported in our study considers both symmetric (Head CT and Brain CT) and asymmetric (Hand X-ray) medical images. The performance of the algorithm was tested visually with various images and empirically with evaluation of parameters.

scholarly journals Identification of Bone Fragmentation in X-Ray Images using Contour Detection Algorithm

2019 ◽  
Vol 8 (9) ◽  
pp. 2121-2124
Keyword(s):  
Edge Detection ◽  
Bone Fracture ◽  
Detection Algorithm ◽  
Contour Detection ◽  
Crack Identification ◽  
Fracture Detection ◽  
Canny Edge Detection ◽  
X Ray ◽  
Base Paper ◽  
Canny Edge

The crack can occur in any bone ofour body. Broken bone is a bone condition that endured a breakdown of bone trustworthiness. The Fracture can't recognize effortlessly by the bare eye, so it is found in the x-beam images. The motivation behind this task is to find the precise territory where the bone fracture happens utilizing X-Ray Bone Fracture Detection by Canny Edge Detection Method. Shrewd Edge Detection technique is an ideal edge identification calculation on deciding the finish of a line with alterable limit and less error rate. The reproduction results have indicated how canny edge detection can help decide area of breaks in x-beam images. In the base paper, the cracked bit is chosen physically to defeat this downside, the proposed technique identify the bone fracture consequently and furthermore it quantifies the parameter like length of the crack, profundity of the fracture and the situation of the crack as for even and vertical pivot. The outcome demonstrates that the proposed technique for crack identification is better. The outcomes demonstrate that calculation is 91% exact and effective

Visual Background Extraction Algorithm Based on Superpixel Information Feedback

2017 ◽  
Vol 37 (7) ◽  
pp. 0715001 ◽  
Author(s):  
陈海永 Chen Haiyong ◽  
郄丽忠 Qie Lizhong ◽  
杨德东 Yang Dedong ◽  
刘 坤 Liu Kun ◽  
李练兵 Li Lianbing
Keyword(s):  
Information Feedback ◽  
Visual Background ◽  
Extraction Algorithm ◽  
Background Extraction

Research on improved edge extraction algorithm of rectangular piece

2018 ◽  
Vol 29 (01) ◽  
pp. 1850007 ◽  
Author(s):  
Yi-Bin He ◽  
Ya-Jun Zeng ◽  
Han-Xin Chen ◽  
San-Xia Xiao ◽  
Yan-Wei Wang ◽  
...  
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Experimental Result ◽  
Structural Elements ◽  
Canny Operator ◽  
Edge Detection Algorithm ◽  
Morphological Gradient ◽  
Extraction Algorithm ◽  
Image Edge ◽  
Rectangular Piece

Traditional edge detection operators such as Prewitt operator, LOG operator and Canny operator, etc. cannot meet the requirements of the modern industrial measurement. This paper proposes a kind of image edge detection algorithm based on improved morphological gradient. It can be detect the image using structural elements, which deals with the characteristic information of the image directly. Choosing different shapes and sizes of structural elements to use together, the ideal image edge information can be detected. The experimental result shows that the algorithm can well extract image edge with noise, which is clearer, and has more detailed edges compared with the previous edge detection algorithm.

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