Abstract
This article presents a fully functional GPU-based implementation of Scale Invariant Feature Transform (SIFT) algorithm. SIFT is a popular image feature extraction algorithm. Although it is a powerful algorithm for image matching but it is also computationally very expensive. This makes it difficult to use especially in real time applications. We purpose to expedite SIFT through GPU-based implementation. There has been some related works on this issue since SIFT was introduced. Our focus is solely on describing GPU-based implementation. We will discuss our implementation in detail. Our implementation is simpler and more efficient than previous works. Part of this paper‟s purpose is to discuss challenges and strategies related to implementing SIFT like image processing algorithms on GPU. In addition, we are going to present a full comparison between serial implementations of SIFT and our GPU-based implementation, namely siftCU, both in accuracy and time consumption.
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