基于模糊超像素中心和非线性扩散滤波的主动轮廓模型实例分割

IF 5.6 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Yiyang Chen;Fuzheng Zhang;Guina Wang;Guirong Weng;Daniele Fontanelli
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引用次数: 0

摘要

主动轮廓模型(ACM)的主要缺点是轮廓的手动设置和不能处理包含复杂信息的图像,限制了其效率和应用范围。本文将模糊超像素中心(FSCs)和非线性扩散滤波器(NDF)结合在一起,提出了一种名为FSC&NDF的ACM,同时解决了上述两个问题。采用YOLOv9定位感兴趣的超像素;这些超像素的联合边界被设置为接近目标形态特征的初始轮廓。采用改进的模糊超像素聚类提取图像特征,生成超像素中心,并将聚类整合到能量函数主体中,NDF模块进一步增强边界定位,抑制噪声。此外,所提出的连接机制使得将对象检测转换为实例分割成为可能。实验结果表明,FSC&NDF克服了以往acm各方面的局限性,其FPS、AP、AP50和$\ mathm {AP}_{M}$均高于主流深度学习算法。基于远心透镜的平台实验进一步证明了FSC&NDF的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Active Contour Model Based on Fuzzy Superpixel Centers and Nonlinear Diffusion Filter for Instance Segmentation
The significant weaknesses of the active contour model (ACM) are the manual setting of contour and the inability to process images with complex information, which limits its efficiency and application scope. In this article, an ACM, called FSC&NDF, is combined with fuzzy superpixel centers (FSCs) and nonlinear diffusion filter (NDF) to solve the above two problems simultaneously. YOLOv9 is adopted to locate the superpixels of interest; the joint boundaries of these superpixels are set as the initial contour, which is close to the morphological features of the target. Improved fuzzy superpixel clustering is applied to extract image features and yield superpixel centers, and the clusters are integrated into the main body of the energy function, NDF module further enhances boundary positioning and suppresses noise. In addition, the proposed connection mechanism makes it possible to convert object detection to instance segmentation. Experimental results show that FSC&NDF overcomes the limitations of previous ACMs in all aspects and its FPS, AP, AP50, and $\mathrm {AP}_{M}$ are higher than mainstream deep learning algorithms. The platform experiment based on the telecentric lens further proves the practicality of FSC&NDF.
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来源期刊
IEEE Transactions on Instrumentation and Measurement
IEEE Transactions on Instrumentation and Measurement 工程技术-工程:电子与电气
CiteScore
9.00
自引率
23.20%
发文量
1294
审稿时长
3.9 months
期刊介绍: Papers are sought that address innovative solutions to the development and use of electrical and electronic instruments and equipment to measure, monitor and/or record physical phenomena for the purpose of advancing measurement science, methods, functionality and applications. The scope of these papers may encompass: (1) theory, methodology, and practice of measurement; (2) design, development and evaluation of instrumentation and measurement systems and components used in generating, acquiring, conditioning and processing signals; (3) analysis, representation, display, and preservation of the information obtained from a set of measurements; and (4) scientific and technical support to establishment and maintenance of technical standards in the field of Instrumentation and Measurement.
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