A Novel Hardware Design for SIFT Generation with Reduced Memory Requirement

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Provided by: Journal of Semiconductor Technology and Science (JSTS)
Topic: Hardware
Format: PDF
Scale Invariant Feature Transform (SIFT) generates image features widely used to match objects in different images. Previous paper on hardware-based SIFT implementation requires excessive internal memory and hardware logic. In this paper, a new hardware organization is proposed to implement SIFT with less memory and hardware cost than the previous paper. To this end, a parallel Gaussian filter bank is adopted to eliminate the buffers that store intermediate results because parallel operations allow all intermediate results available at the same time.
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