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Flood fill mean shift: A robust segmentation algorithm

机译:洪水填充均值漂移:鲁棒的分割算法

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摘要

In this paper, the flood fill mean shift (FFMS) is introduced. This algorithm is developed for robust segmentation by improving the mean shift (MS) through the flood fill (FF) technique, instead of relying on spatial bandwidth. Due to this exchange, the FFMS involves only one parameter, the range bandwidth, which is not sensitive and is able to acquire global characteristics. If the image parts affected by the illumination changes are sufficiently small and their boundaries are not clear, the illumination effects do not influence the mode seeking procedure of the proposed FFMS. To prove the usefulness and the validity of our algorithm, we present several experiments and analysis of the results.
机译:本文介绍了洪水填平平均偏移(FFMS)。通过改进泛洪填充(FF)技术的均值漂移(MS)而不是依赖于空间带宽,开发了该算法用于鲁棒分割。由于这种交换,FFMS仅涉及一个参数,即范围带宽,该参数不敏感并且能够获取全局特性。如果受照度变化影响的图像部分足够小并且边界不清晰,则照度效果不会影响所提出的FFMS的模式搜索过程。为了证明该算法的有效性和有效性,我们提出了一些实验和结果分析。

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