润滑与密封
潤滑與密封
윤활여밀봉
LUBRICATION ENGINEERING
2014年
12期
101-104,109
,共5页
K-means聚类%Lab颜色空间%最大类间方差法
K-means聚類%Lab顏色空間%最大類間方差法
K-means취류%Lab안색공간%최대류간방차법
K-means clustering%Lab color space%Ostu method
针对在HSI颜色空间下存在的图像的二维颜色分量分布散乱不紧密，存在聚类中心计算错误，利用二维颜色分量很难将背景和磨粒准确分割开，分割完的铁谱图像仍包含许多不需要的微小磨粒等问题，提出采用K-means聚类与最大类间方差的图像分割方法。分别选取球粒、切削磨粒、严重滑动磨粒、红色氧化物、疲劳磨粒的彩色图像，在Lab颜色空间下利用二维颜色分量进行聚类分析及最大类间方差阈值分割，并进行三维数学形态学处理。结果表明，提出的方法实现了小磨粒与目标磨粒的有效分割，可以得到较为完整的彩色磨粒图像，为磨粒的颜色参数识别提供有效的依据。
針對在HSI顏色空間下存在的圖像的二維顏色分量分佈散亂不緊密，存在聚類中心計算錯誤，利用二維顏色分量很難將揹景和磨粒準確分割開，分割完的鐵譜圖像仍包含許多不需要的微小磨粒等問題，提齣採用K-means聚類與最大類間方差的圖像分割方法。分彆選取毬粒、切削磨粒、嚴重滑動磨粒、紅色氧化物、疲勞磨粒的綵色圖像，在Lab顏色空間下利用二維顏色分量進行聚類分析及最大類間方差閾值分割，併進行三維數學形態學處理。結果錶明，提齣的方法實現瞭小磨粒與目標磨粒的有效分割，可以得到較為完整的綵色磨粒圖像，為磨粒的顏色參數識彆提供有效的依據。
침대재HSI안색공간하존재적도상적이유안색분량분포산란불긴밀，존재취류중심계산착오，이용이유안색분량흔난장배경화마립준학분할개，분할완적철보도상잉포함허다불수요적미소마립등문제，제출채용K-means취류여최대류간방차적도상분할방법。분별선취구립、절삭마립、엄중활동마립、홍색양화물、피로마립적채색도상，재Lab안색공간하이용이유안색분량진행취류분석급최대류간방차역치분할，병진행삼유수학형태학처리。결과표명，제출적방법실현료소마립여목표마립적유효분할，가이득도교위완정적채색마립도상，위마립적안색삼수식별제공유효적의거。
The images under the HSI color space distribution of two dimensional color component scattered were not tight and existing clustering center calculation error,it was difficult to accurately separate background and debris using two dimensional color component,and the segmented ferrographic images still contained many tiny debris which were not nee-ded.The image segmentation by K-means Clustering and the between-cluster variance method was put forward.Spherical particles,cutting particles,severe sliding particles,red oxide particles,fatigue particles were selected to segment by cluste-ring and Ostu method under Lab color space’s two dimensional color component,and segmented images were dealt with three-dimensional mathematical morphology method.The results show that the proposed method can achieve effective seg-mentation between tiny debris and target debris,and can obtain a more complete color wear particle images,it provides ef-fective basis for identification of the color parameters of debris.
