JOURNAL ARTICLE

Image Mosaic Based on SURF Feature Matching

Abstract

In the paper, an image mosaic algorithm based on SURF feature matching is proposed. The algorithm uses SURF operator which has strong robustness and superior performance to extract features instead of conventional SIFT operator. The extracted features are matched by a novel matching scheme - fast bidirectional matching. Then a RANSAC algorithm is applied to eliminate outliers and obtain the transformation matrix between images. Finally images are stitched by a multi-band blending algorithm. The presented algorithm overcomes the disadvantages of the traditional image mosaic methods which are susceptible to different scale and moving objects, and has a great improvement in calculation speed. Experimental results show that the method with strong robustness performs fast and effectively.

Keywords:
RANSAC Scale-invariant feature transform Robustness (evolution) Artificial intelligence Computer science Computer vision Outlier Matching (statistics) Pattern recognition (psychology) Feature extraction Operator (biology) Image matching Algorithm Image (mathematics) Mathematics

Metrics

13
Cited By
0.62
FWCI (Field Weighted Citation Impact)
9
Refs
0.77
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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