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In this paper, we examined heterogeneous architectures, for their suitability to run the scale invariant feature transformation (SIFT) algorithm in real time. The SIFT is one of the most robust as well as one of the most computational intensive algorithms to extract local features in many machine-vision applications. Many ongoing researches presented methods on improving the SIFT execution time. However,...
Local feature extraction is one of the most important steps in image processing applications such as image matching and object recognition. The Scale Invariant Feature Transformation (SIFT) algorithm is one of the most robust as well as one of the most computation intensive algorithms to extract local features. Recent implementations of the algorithm focus on homogeneous processors like multi-core...
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