An Automatic Feature Extraction Method Based on Multiple Sensors

2019 ◽  
Author(s):  
Weiwei Sun ◽  
Min Huang ◽  
Yiqian He
Keyword(s):  
Feature Extraction ◽  
Extraction Method ◽  
Feature Extraction Method ◽  
Multiple Sensors ◽  
Automatic Feature Extraction

scholarly journals An automatic feature extraction method and its application in fault diagnosis

2017 ◽  
Vol 19 (4) ◽  
pp. 2521-2533 ◽  
Author(s):  
Shunming Li ◽  
Jinrui Wang ◽  
Xingxing Jiang ◽  
Chun Cheng
Keyword(s):  
Feature Extraction ◽  
Fault Diagnosis ◽  
Extraction Method ◽  
Feature Extraction Method ◽  
Automatic Feature Extraction

A Rapid and Automatic Feature Extraction Method for Artificial Targets Used in Industrial Photogrammetry Applications

2012 ◽  
Vol 170-173 ◽  
pp. 2995-2998
Author(s):  
Jian Wei Liu ◽  
Zhi Qiang Jiang ◽  
Hao Hu ◽  
Xin Yin
Keyword(s):  
Feature Extraction ◽  
Reference Point ◽  
Extraction Method ◽  
Target Location ◽  
Reference Points ◽  
Improved Method ◽  
Feature Extraction Method ◽  
Automatic Feature Extraction ◽  
Centroid Algorithm ◽  
Point Detection

Distributing artificial targets on the object to be measured is a reliable and common method for achieving optimum target location and accurate correspondence among multi-view images, which are universally adopted in industrial photogrammetry applications. In this paper artificial circular un-coded targets and coded targets are used as reference points, an automatic and rapid algorithm for reference point detection is proposed. Targets are extracted from the images according to their size, shape, intensity , etc. An improved method to identify the ID of the coded target is proposed. The gray scale centroid algorithm is applied to get sub-pixel locations of both un-coded and coded targets. Practical examples show that the algorithm can identify and locate artificial targets in images quickly and accurately. It is robust to the change of projection angles and noise.

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