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An FPGA acceleration of a level set segmentation method

Authors: Haruhisa Tsuyama; Tsutomu Maruyama;

An FPGA acceleration of a level set segmentation method

Abstract

Image segmentation is one of the most important tasks in the image processing. The level set method is a powerful algorithm for the segmentation. In the level set method, a three-dimensional auxiliary function is used for detecting objects of various shapes. Its computational complexity is, however, very high, and many techniques have been proposed to reduce the computational complexity. In this paper, we describe a new algorithm for the level set method and its FPGA implementation. This algorithm is (1) designed so as to allow deep pipelining on hardware systems, and (2) able to detect all objects in the image, which is difficult for previous level set algorithms. We have implemented the algorithm on Xilinx XC4VLX160, and its performance is about 700 fps for 640 × 480 pixel images.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
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