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Survey of Scale-invariant Feature Transform Algorithm | ||
| Iraqi Journal of Science | ||
| Article 1, Volume 58, Issue 1, 2018, Pages 292-301 | ||
| Authors | ||
| Eklas khlaf Egbash; Suha Mohammad | ||
| Abstract | ||
| The effectiveness of detecting and matching of image features using multiple views of a specified scene using dynamic scene analysis is considered to be a critical first step for many applications in computer vision image processing. The Scale invariant feature transform (SIFT) can be applied very successfully of typical images captured by a digital camera. In this paper, firstly the SIFT and its variants are systematically analyzed. Then, the performances are evaluated in many situations: change in rotation, change in blurs, change in scale and change in illumination. The outcome results show that each algorithm has its advantages when compared with other algorithms. | ||
| Keywords | ||
| Feature Detection; Feature Descriptor; matching | ||
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