Real time image mosaicing system based on feature extraction techniques
| Autor: | Hazem M. El-Bakry, Ebtsam Adel, Mohammed Elmogy |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
business.industry
Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-invariant feature transform Kanade–Lucas–Tomasi feature tracker Pattern recognition Computer graphics Image stitching Automatic image annotation Robustness (computer science) Direct methods Computer vision Artificial intelligence business |
| Zdroj: | 2014 9th International Conference on Computer Engineering & Systems (ICCES). |
| Popis: | Image mosaicing/stitching is considered as an active research area in computer vision and computer graphics. Image mosaicing is concerned with combining two or more images of the same scene into one panoramic image with high resolution. There are two main types of techniques used for creating image stitching: direct methods and feature-based methods. The greatest advantages of feature-based methods over the other methods are their speed, robustness, and the availability of creating panoramic image of a non-planar scene with unrestricted camera motion. In this paper, we propose a real time image stitching system based on ORB feature-based technique. We compared the performance of our proposed system with SIFT and SURF feature-based techniques. The experiment results show that the ORB algorithm is the fastest, the highest performance, and it needs very low memory requirements. In addition, we make a comparison between different feature-based detectors. The experimental result shows that SIFT is a robust algorithm but it takes more time for computations. MSER and FAST techniques have better performance with respect to speed and accuracy. |
| Databáze: | OpenAIRE |
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