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Pavement image segmentation based on fast FCM clustering with spatial information in internet of things

机译:基于快速FCM聚类并结合物联网中空间信息的路面图像分割

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摘要

Pavement image segmentation needs to deal with noise spots and has real time requirement. The original FCM method only considers the pixel's gray value and doesn't fully utilize the spatial information of the image. A new fast FCM algorithm is proposed, and it has noise immunity. By comparing with other FCM algorithms, it achieves better segmentation results through less iteration times and more rapid runtime. It is an effective and noise-resistant algorithm for pavement image segmentation from video multimedia in IOT (internet of things) platform.
机译:路面图像分割需要处理噪点并具有实时性。原始的FCM方法仅考虑像素的灰度值,并未充分利用图像的空间信息。提出了一种新的快速FCM算法,该算法具有抗扰性。与其他FCM算法相比,它通过更少的迭代时间和更快的运行时间来获得更好的分割结果。它是一种有效的抗噪算法,用于在物联网平台上从视频多媒体中分割路面图像。

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