Study on Infrared Thermography Mosaic Algorithm Based on the Feature Point Detection and Registration

2012 ◽  
Vol 594-597 ◽  
pp. 1138-1142
Author(s):  
Ji Tong Jiang ◽  
Chao Song ◽  
Jun An
Keyword(s):  
Image Fusion ◽  
Infrared Thermography ◽  
Feature Detection ◽  
Feature Point ◽  
Thermal Method ◽  
Image Mosaic ◽  
Image Transformation ◽  
Feature Registration ◽  
Infrared Thermograph ◽  
Point Detection

When detecting the large objects by infrared thermal method, it is difficult to get a whole panoramic picture. So it needs to stitch some infrared thermography. Image mosaic includes 4 steps, feature detection, feature registration, image transformation and image fusion. This paper studies about an infrared thermograph mosaic algorithm based on the feature point detection and registration, and realizes it in MATLAB.

A Rapid and Efficient Feature Point Detection and Matching Algorithm

2014 ◽  
Vol 607 ◽  
pp. 641-646
Author(s):  
Xiao Ling Ding ◽  
Qiang Zhao ◽  
Yi Bin Li ◽  
Xin Ma
Keyword(s):  
Computer Vision ◽  
Vision Research ◽  
Feature Detection ◽  
Feature Point ◽  
Sift Algorithm ◽  
Matching Algorithm ◽  
Object Feature ◽  
Point Detection ◽  
Real Time Application ◽  
Fast Detector

In the field of computer vision research, object feature detection and matching algorithm become a hot. Aiming at SIFT algorithm and SURF algorithm cannot meet the needs of real-time application, a feature point detection and matching algorithm based on orient FAST detector and rotation BRIEF descriptor is used. The experiments demonstrate that, this method not only remains the advantages of SURF but also improves the detection speed, and it can fully applicable to the field of computer vision to detect moving targets.

scholarly journals Illumination-Invariant Feature Point Detection Based on Neighborhood Information

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6630
Author(s):  
Ruiping Wang ◽  
Liangcai Zeng ◽  
Shiqian Wu ◽  
Wei Cao ◽  
Kelvin Wong
Keyword(s):  
Feature Detection ◽  
Detection Method ◽  
Experimental Results ◽  
Feature Point ◽  
Detection Methods ◽  
Feature Points ◽  
Illumination Invariant ◽  
Neighborhood Information ◽  
Invariant Feature ◽  
Point Detection

Feature point detection is the basis of computer vision, and the detection methods with geometric invariance and illumination invariance are the key and difficult problem in the field of feature detection. This paper proposes an illumination-invariant feature point detection method based on neighborhood information. The method can be summarized into two steps. Firstly, the feature points are divided into eight types according to the number of connected neighbors. Secondly, each type of feature points is classified again according to the position distribution of neighboring pixels. The theoretical deduction proves that the proposed method has lower computational complexity than other methods. The experimental results indicate that, when the photometric variation of the two images is very large, the feature-based detection methods are usually inferior, while the learning-based detection methods performs better. However, our method performs better than the learning-based detection method in terms of the number of feature points, the number of matching points, and the repeatability rate stability. The experimental results demonstrate that the proposed method has the best illumination robustness among state-of-the-art feature detection methods.

Tele-Operation of Robot using Facial Feature Point Detection

2019 ◽  
Author(s):  
Masahiko Minamoto ◽  
Hidaka Sato ◽  
Takahiro Kanno ◽  
Tetsuro Miyazaki ◽  
Toshihiro Kawase ◽  
...  
Keyword(s):  
Facial Feature ◽  
Feature Point ◽  
Point Detection

Substation Remote Viewing Image Mosaic Based on Fuzzy Cellular Automata Detection

2013 ◽  
Vol 846-847 ◽  
pp. 1213-1216
Author(s):  
Hong Tao Zai
Keyword(s):  
Cellular Automata ◽  
Feature Point ◽  
Image Mosaic ◽  
Feature Points ◽  
System A ◽  
Safety And Reliability ◽  
Fuzzy Cellular Automata ◽  
Remote Viewing ◽  
Matched Edge ◽  
Edge Feature

In order to improve the effect of remote video monitoring system, a new image mosaic technology based on fuzzy cellular automata detection is presented. Firstly, the edge feature points from two images are extracted by fuzzy cellular automata; secondly, the corresponding feature point pairs are got by the cross-correlation of the gray scale around the edge feature points; finally the images can be stitched by matched edge feature point pairs. The experiment of remote viewing image mosaic in substation shows that this method can achieve image mosaic effectively and it will be benefit to improve the safety and reliability of substation operation.

scholarly journals Multi-Focus Image Fusion With Point Detection Filter and Superpixel-Based Consistency Verification

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 99956-99973
Author(s):  
Qiang Chen ◽  
Bin Yang ◽  
Yuehua Li ◽  
Lihui Pang
Keyword(s):  
Image Fusion ◽  
Focus Image ◽  
Point Detection ◽  
Consistency Verification ◽  
Detection Filter
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