查询结果:   郭恒光,瞿军,汪兴海.基于分形特征的磨粒图像分割[J].计算机应用与软件,2014,31(5):234 - 236.
中文标题
基于分形特征的磨粒图像分割
发表栏目
图像处理与应用
摘要点击数
775
英文标题
WEAR PARTICLE IMAGE SEGMENTATION BASED ON FRACTAL FEATURE
作 者
郭恒光 瞿军 汪兴海 Guo Hengguang Qu Jun Wang Xinghai
作者单位
海军航空工程学院研究生管理大队 山东 烟台 264000 海军航空工程学院飞行器工程系 山东 烟台 264000 海军航空工程学院基础实验部 山东 烟台 264000   
英文单位
Graduate Students’ Brigade,Naval Aeronautical Engineering Institute,Yantai 264000,Shandong,China Department of Airborne Vehicle Engineering,Naval Aeronautical Engineering Institute,Yantai 264000,Shandong,China Department of Basic Experiment,Naval Aeronautical Engineering Institute,Yantai 264000,Shandong,China   
关键词
分形特征 自组织特征映射神经网络 磨粒图像分割
Keywords
Fractal features Self- organising feature mapping neural network Wear particle image segmentation
基金项目
作者资料
郭恒光,博士生,主研领域:机械系统故障诊断理论与技术。瞿军,教授。汪兴海,硕士。 。
文章摘要
磨粒图像分割是磨粒图像分析的关键一步,分割结果的准确性将直接影响磨粒的最终识别和分类。分形理论在表征磨粒的轮廓特征和表面特征方面得到了广泛应用。结合磨粒图像的分形特征和自组织特征映射神经网络,提出基于分形特征的磨粒图像分割方法。首先,计算磨粒图像的分形维数,多重分形维数,结合图像的灰度信息,共得到图像的8个特征;然后,利用自组织特征映射神经网络的自组织、自学习特性,实现磨粒图像的分割。磨粒图像分割的结果表明,该算法是可行的、有效的。
Abstract
Wear particle image segmentation is the key step of wear particle image analysis, and the accuracy of the segmentation result affects directly the final recognition and classification of wear particles. Fractal geometry has been used widely in characterising wear particle profile and surface features. We propose a fractal features-based wear particle image segmentation method by combining the fractal features of ware particle image with self-organising feature mapping (SOFM) neural network. First, we calculate the fractal dimensions and multi-fractal dimensions of the ware particle image, in combination with its grey information, we acquire total eight features of the image. Then, we use the characteristics of self-organising and self-learning of SOFM neural network to implement the wear particle image segmentation. Result of the wear particle image segmentation shows that this algorithm is feasible and effective.
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