近海环境中气味源识别的迭代模糊分割算法

Wei Li
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引用次数: 8

摘要

在近岸和海洋环境中,化学羽流追踪(CPT)的任务是驾驶自主水下航行器(AUV)寻找化学羽流,追踪羽流的来源,并宣布源位置。有必要使用视觉系统来识别申报的气味来源。在宣布震源时,在近岸海洋环境中拍摄的彩色图像由于昏暗的照明条件和流体平流效应而非常模糊。本文提出了一种迭代模糊分割(IFS)算法,用于提取化学羽流和气味源的颜色成分,以视觉确认正确申报的气味源。所提出的方法可能会引起图像处理和计算机视觉领域的普遍兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Iterative Fuzzy Segmentation Algorithm for Recognizing an Odor Source in Near Shore Ocean Environments
A mission of chemical plume tracing (CPT) in near-shore and ocean environments is to navigate an autonomous underwater vehicle (AUV) to find a chemical plume, to trace the plume to its source, and to declare the source location. It is necessary to recognize the declared odor source by using a visual system. Color images, which were taken in near-shore ocean environments when the source was declared, are very vague due to dim illumination conditions and fluid advection effects. This paper presents an iterative fuzzy segmentation (IFS) algorithm for extracting color components of the chemical plume and the odor source for visual confirmation of the correct declared odor source. The proposed approach might be of general interest in image processing and computer vision.
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