The Image Forest Transform Architecture
作者： Fabio A.M. Cappabianco , Guido Araujo , Alexandre X. Falcao
关键词: Image processing 、 Scale-invariant feature transform 、 Computational science 、 Edge detection 、 Digital image processing 、 Binary image 、 Feature detection (computer vision) 、 Computer science 、 Computer vision 、 Field-programmable gate array 、 Artificial intelligence 、 Top-hat transform
摘要: The image foresting transform (IFT) is e a generic technique that uses simple variations of the same core algorithm to construct many processing operators like watershed transforms, edge tracking, geodesic paths, among others. In this paper we propose silicon IFT (SIFT), an FPGA-based architecture leverages on flexibility build fast capable implementing in hardware. Our experiments have shown SIFT can reach speedups 5600 upon correspondent software implementation. Moreover, they exhibit excellent execution times as compared recent dedicated architectures.
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