Terminal Aimpoint Selection Algorithm Based on Convex Hull Technique

2014 ◽  
Vol 667 ◽  
pp. 264-268
Author(s):  
Xuan Wang ◽  
Jia Hao Deng ◽  
Gui Yan Kou
Keyword(s):  
Convex Hull ◽  
Real Time ◽  
Pattern Matching ◽  
Corner Detection ◽  
Target Area ◽  
Selection Algorithm ◽  
Boundary Extraction ◽  
Image Preprocessing ◽  
Computation Geometry ◽  
Guidance Systems

A terminal aimpoint selection algorithm is proposed in this paper for selecting the aimpoint precisely in real time. This approach avoids complicated and time-consuming pattern matching or boundary extraction. Through the image preprocessing and corner detection, the convex hull technique is utilized to cover the target area based on Computation Geometry, where centriod of the convex hull is defined as the aimpoint of the target. The proposed algorithm promotes intelligence, efficiency and accuracy of navigation guidance systems, which is proved in the simulation.

scholarly journals Cobb Angle Measurement Method of Scoliosis Based on U-net Network

2021 ◽  
Author(s):  
Jia-Li Cui ◽  
De-Dong Gao ◽  
Sheng-Jun Shen ◽  
Lin-Ze Wang ◽  
Yan Zhao
Keyword(s):  
Convex Hull ◽  
Cobb Angle ◽  
Measurement Method ◽  
Angle Measurement ◽  
Corner Detection ◽  
Target Area ◽  
Important Indicator ◽  
Corner Points ◽  
Cobb Angle Measurement ◽  
Convex Hull Algorithm

Abstract The Cobb angle is an important indicator for judging the severity of scoliosis. However, the segmentation and corner marking methods based on deep learning have problems such as target area segmentation and corner detection blur in the X-ray Cobb angle measurement. In this paper, a new convex hull algorithm to detect the corners and a mask generation strategy are proposed to improve the accuracy of Cobb angle recognition. On this basis, the Cobb angle measurement method is presented to identify and segment the target area based on U-net network, and then combine the new convex hull algorithm to detect corners and mask generation strategies. A total of 68 corner points were marked on 17 vertebrae, and the corner points detected by the markers were used to calculate the Cobb angle. The experimental results have proved that the U-net based measurement method could effectively improve the corner detection accuracy on the basis of segmentation, thereby reducing the calculation error of the Cobb angle. The Cobb mean absolute error (AMAE) is 9.2832°, and the symmetric mean absolute percentage error (SMAPE) is 21.675%, which achieved a relatively good result compared with the measurement by professional orthopaedist in error.

Point pattern matching using convex hull edges

1985 ◽  
Vol SMC-15 (5) ◽  
pp. 631-637 ◽  
Author(s):  
Ardeshir Goshtasby ◽  
George C. Stockman
Keyword(s):  
Convex Hull ◽  
Pattern Matching ◽  
Point Pattern ◽  
Point Pattern Matching
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