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Image segmentation based on the HSI color space and an improved mean shift

机译:基于HSI颜色空间的图像分割和改进的平均移位

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A novel image segmentation algorithm based on the HSI color space and an improved mean shift is proposed. The current work is discussed form two perspectives, i.e., the color space more suitable for human being's perception is selected and the segmentation algorithm is improved sufficiently. Unlike many of the traditional algorithms, the proposed algorithm is nonparametric and does not require any training base or prior knowledge, operates on the image adaptively. Experimental results reveal that the proposed algorithm can achieve better segmentation performance and has a stronger self-adaptability but less complexity than the comparison methods. Moreover, it is shown that the proposed algorithm can be a promising approach and be extended to more related research areas.
机译:提出了一种基于HSI颜色空间的新颖的图像分割算法和改进的平均移位。讨论了当前的作品,形成了两个观点,即选择了更适合于人类感知的颜色空间,并且可以充分提高分割算法。与许多传统算法不同,所提出的算法是非参数,并且不需要任何训练基础或先前知识,适自动化图像。实验结果表明,所提出的算法可以实现更好的分割性能,具有更强的自适应性,但比比较方法更不复杂。此外,示出所提出的算法可以是有希望的方法,并扩展到更多相关的研究领域。

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