Scale Invariant Feature Transform Based Image Matching and Registration
| Autor: | Heena R. Kher, V. K. Thakar |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
business.industry
Template matching Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Corner detection Top-hat transform Image registration Pattern recognition Scale space Feature (computer vision) Computer Science::Computer Vision and Pattern Recognition Computer vision Artificial intelligence business Image restoration Mathematics |
| Zdroj: | 2014 Fifth International Conference on Signal and Image Processing. |
| DOI: | 10.1109/icsip.2014.12 |
| Popis: | This paper presents Image matching and registration method that is invariant to scale, rotation, translation and illumination changes. The method is named as Scale Invariant Feature Transform (SIFT). This algorithm will detect and describe image features such as contours, points, corners etc. SIFT descriptors are the characteristic signature of the feature. The features calculated from the image to be registered should be distinctive and then it can be matched. It can be useful in object recognition, image mosaicing, 3 D reconstruction and video tracking. The simulation results shows that this algorithm works well in all types of cases having scale and rotation difference, it also register the object having occlusion and clutter background. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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