Fetal skull analysis in ultrasound images based on iterative randomized Hough transform

2009 ◽  
Author(s):  
Yufei Shen ◽  
Jinhua Yu ◽  
Yuzhong Shen ◽  
Yuanyuan Wang
Keyword(s):  
Hough Transform ◽  
Ultrasound Images ◽  
Randomized Hough Transform

Coarse-To-Fine 3D Randomized Hough Transform for Dim Target Detection

2014 ◽  
Vol 519-520 ◽  
pp. 1040-1045
Author(s):  
Ling Fan
Keyword(s):  
Target Detection ◽  
Hough Transform ◽  
Constant Velocity ◽  
Three Dimensional ◽  
Randomized Hough Transform ◽  
Straight Line ◽  
Memory Complexity ◽  
Coarse To Fine

This paper makes some improvements on Roberts representation for straight line in space and proposes a coarse-to-fine three-dimensional (3D) Randomized Hough Transform (RHT) for the detection of dim targets. Using range, bearing and elevation information of the received echoes, 3D RHT can detect constant velocity target in space. In addition, this paper applies a coarse-to-fine strategy to the 3D RHT, which aims to solve both the computational and memory complexity problems. The validity of the coarse-to-fine 3D RHT is verified by simulations. In comparison with the 2D case, which only uses the range-bearing information, the coarse-to-fine 3D RHT has a better practical value in dim target detection.

scholarly journals Faster and optimal detection of parametric shapes

2021 ◽  
Author(s):  
Shynimol E. Thayilchira
Keyword(s):  
Probability Theory ◽  
Image Analysis ◽  
Computational Complexity ◽  
Hough Transform ◽  
Cross Entropy ◽  
Optimal Detection ◽  
Time Efficiency ◽  
Generalized Hough Transform ◽  
Randomized Hough Transform ◽  
Complex Image

In this project, an analysis of the faster detection of shapes using Randomized Hough Transform (RHT) was investigated. Since reduced computational complexity and time efficiency are the major concerns for complex image analysis, the focus of the research was to investigate RHT for these specific tasks. Also, a detailed analysis of probability theory associated with RHT theory was investigated as well. Thus effectiveness of RHT was proven mathematically in this project. In this project, RHT technique combined with Generalized Hough Transform (GHT) using Newton's curve fitting technique was proposed for faster detection of shapes in the Hough Domain. Finally, the image under question was enhanced using Minimum Cross-Entropy Optimization to further enhance the image and then RGHT process was carried out. This helped the RGHT process to obtain the required time efficiency.

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