Title
Image mosaicing of tunnel wall images using high level features
Abstract
This paper proposes a novel approach for position offset correction of images taken from a moving robotic platform in tunnel environments using image mosaicing. An image mosaic is formed by combining multiple images which capture overlapping components of a scene into a larger image. Unlike current image mosaicing methods, which use low-level features such as corners, our method uses binary edges as high-level features for image registration via template matching. This is necessary since such low-level features are absent or rare in tunnel environments. A shading correction algorithm is applied as a pre-processing step to adjust the uneven illumination present in this environment. This technique is simple and efficient while being robust to small camera rotations and small variations in camera distance from the wall. Experimental results show that our method contributes to good image mosaicing results with a low computational complexity, which is attractive for real-time image-based inspection applications.
Year
DOI
Venue
2017
10.1109/ISPA.2017.8073585
Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis
Keywords
Field
DocType
image alignment,image blending,image stitching
Template matching,Histogram,Computer vision,Image stitching,Computer science,Image processing,Feature extraction,Image segmentation,Artificial intelligence,Image registration,Offset (computer science)
Conference
ISSN
ISBN
Citations 
1845-5921
978-1-5090-4012-4
0
PageRank 
References 
Authors
0.34
7
4
Name
Order
Citations
PageRank
Leanne Attard101.35
Carl James Debono23811.66
Gianluca Valentino301.69
Mario Di Castro4105.79