scholarly journals Automation of Thermographic 3D Modelling through Image Fusion and Image Matching Techniques

2011 ◽  
Author(s):  
S. Laguela ◽  
J. Armesto ◽  
H. Gonzalez-Jorge ◽  
P. Arias ◽  
J. Herraez
Keyword(s):  
Image Fusion ◽  
Image Matching ◽  
3D Modelling ◽  
Matching Techniques

Automation of thermographic 3D modelling through image fusion and image matching techniques

2012 ◽  
Vol 27 ◽  
pp. 24-31 ◽  
Author(s):  
S. Lagüela ◽  
J. Armesto ◽  
P. Arias ◽  
J. Herráez
Keyword(s):  
Image Fusion ◽  
Image Matching ◽  
3D Modelling ◽  
Matching Techniques

scholarly journals AN INTEGRATED PHOTOGRAMMETRIC AND PHOTOCLINOMETRIC APPROACH FOR PIXEL-RESOLUTION 3D MODELLING OF LUNAR SURFACE

2018 ◽  
Vol XLII-3 ◽  
pp. 1117-1122
Author(s):  
W. C. Liu ◽  
B. Wu
Keyword(s):  
High Resolution ◽  
Lunar Surface ◽  
Image Matching ◽  
Point Cloud ◽  
3D Modelling ◽  
Conjugate Points ◽  
Stereo Pair ◽  
Pixel Resolution ◽  
Dense Image ◽  
Lunar Reconnaissance Orbiter

High-resolution 3D modelling of lunar surface is important for lunar scientific research and exploration missions. Photogrammetry is known for 3D mapping and modelling from a pair of stereo images based on dense image matching. However dense matching may fail in poorly textured areas and in situations when the image pair has large illumination differences. As a result, the actual achievable spatial resolution of the 3D model from photogrammetry is limited by the performance of dense image matching. On the other hand, photoclinometry (i.e., shape from shading) is characterised by its ability to recover pixel-wise surface shapes based on image intensity and imaging conditions such as illumination and viewing directions. More robust shape reconstruction through photoclinometry can be achieved by incorporating images acquired under different illumination conditions (i.e., photometric stereo). Introducing photoclinometry into photogrammetric processing can therefore effectively increase the achievable resolution of the mapping result while maintaining its overall accuracy. This research presents an integrated photogrammetric and photoclinometric approach for pixel-resolution 3D modelling of the lunar surface. First, photoclinometry is interacted with stereo image matching to create robust and spatially well distributed dense conjugate points. Then, based on the 3D point cloud derived from photogrammetric processing of the dense conjugate points, photoclinometry is further introduced to derive the 3D positions of the unmatched points and to refine the final point cloud. The approach is able to produce one 3D point for each image pixel within the overlapping area of the stereo pair so that to obtain pixel-resolution 3D models. Experiments using the Lunar Reconnaissance Orbiter Camera - Narrow Angle Camera (LROC NAC) images show the superior performances of the approach compared with traditional photogrammetric technique. The results and findings from this research contribute to optimal exploitation of image information for high-resolution 3D modelling of the lunar surface, which is of significance for the advancement of lunar and planetary mapping.

scholarly journals In vivo kinematics of gait in posterior-stabilized and bicruciate-stabilized total knee arthroplasties using image-matching techniques

2018 ◽  
Vol 42 (11) ◽  
pp. 2573-2581 ◽  
Author(s):  
Koji Murakami ◽  
Satoshi Hamai ◽  
Ken Okazaki ◽  
Yifeng Wang ◽  
Satoru Ikebe ◽  
...  
Keyword(s):  
Image Matching ◽  
Total Knee Arthroplasties ◽  
Posterior Stabilized ◽  
In Vivo Kinematics ◽  
Total Knee ◽  
Matching Techniques

Angle-distance image matching techniques for protein structure comparison

2008 ◽  
Vol 21 (6) ◽  
pp. 442-452 ◽  
Author(s):  
Chia-Han Chu ◽  
Chuan Yi Tang ◽  
Cheng-Yin Tang ◽  
Tun-Wen Pai
Keyword(s):  
Protein Structure ◽  
Image Matching ◽  
Structure Comparison ◽  
Protein Structure Comparison ◽  
Matching Techniques

scholarly journals 3D modelling of trompe l'oeil decorated vaults using dense matching techniques

2014 ◽  
Vol II-5 ◽  
pp. 97-104 ◽  
Author(s):  
F. Chiabrando ◽  
A. Lingua ◽  
F. Noardo ◽  
A. Spano
Keyword(s):  
Detailed Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Software Tools ◽  
3D Modelling ◽  
Complex Objects ◽  
Trompe L'oeil ◽  
Dense Matching ◽  
Automatic Matching ◽  
Matching Techniques

Dense matching techniques, implemented in many commercial and open source software, are useful instruments for carrying out a rapid and detailed analysis of complex objects, including various types of details and surfaces. For this reason these tools were tested in the metric survey of a frescoed ceiling in the hall of honour of a baroque building. The surfaces are covered with trompe-l’oeil paintings which theoretically can give a very good texture to automatic matching algorithms but in this case problems arise when attempting to reconstruct the correct geometry: in fact, in correspondence with the main architectonic painted details, the models present some irregularities, unexpectedly coherent with the painted drawing. The photogrammetric models have been compared with data deriving from a LIDAR survey of the same object, to evaluate the entity of this blunder: some profiles of selected sections have been extracted, verifying the different behaviours of the software tools.

scholarly journals Multi Sensor Image Matching using Super Symmetric Affinity Tensors based HyperGraph Matching

2019 ◽  
Vol 8 (2) ◽  
pp. 6161-6166
Keyword(s):  
Image Matching ◽  
Third Order ◽  
Good Recall ◽  
Hypergraph Matching ◽  
Sensing Applications ◽  
Performance Accuracy ◽  
Matching Technique ◽  
Multiple Sensor ◽  
Remote Sensing Applications ◽  
Matching Techniques

Image Matching technique is regularly on one of the main errands in numerous Photogrammetry and Remote Sensing applications. Based on multi-discipline, the approach of multiple sensor image matching is a novel one established which has vital application in military, civil, medicinal, and certain other domains. However, image matching approach faces numerous challenges, specifically in multi-sensor images where the images are gathered from the different sensor with different intensities, scales, and moments. Thus, a novel image matching approach is introduced in this paper using affinity tensor and HyperGraph Matching (HGM) technique that attempts to overcome certain drawbacks in matching and increases performance accuracy. Hypergraph matching techniques are employed using affinity tensors and consider supersymmetric property during construction. Graphs are constructed using graph theory for both sources, and target image and matching is done using third-order tensors. The experimental outcomes displayed that the proposed technique has good recall, precision, and positive accuracy values compared to the existing two descriptors based and tensor-based matching algorithms.

Sign in / Sign up

Export Citation Format

Share Document