红外与激光工程
紅外與激光工程
홍외여격광공정
INFRARED AND LASER ENGINEERING
2013年
10期
2682-2686,2696
,共6页
距离选通%图像分割%模糊C均值聚类%Otsu法%初定位
距離選通%圖像分割%模糊C均值聚類%Otsu法%初定位
거리선통%도상분할%모호C균치취류%Otsu법%초정위
range-gated%image segmentation%fuzzy C- means clustering%Otsu%pre-positioning
针对距离选通激光成像对比度低、照度不均、图像模糊的特点,提出了一种基于空间定位的模糊C均值聚类方法( SPFCM )对目标进行分割。传统的模糊C均值聚类法存在以下缺点:一是需要预先获得目标分类数量,自适应性较差;二是对空间信息不敏感,导致目标轮廓不完整以及错误分类。针对上述缺陷,文中对传统算法进行了改进,引入了初定位的概念,首先利用最大类间方差法(Otsu法)和数学形态学工具对子目标进行初步定位,再将其形心方位信息和灰度信息融合到聚类过程中,以较短的迭代过程实现不同目标的归类。实验结果证明基于空间定位的模糊C均值聚类法可以完整、有效地对距离选通激光图像进行提取分割,处理时间优于传统FCM。
針對距離選通激光成像對比度低、照度不均、圖像模糊的特點,提齣瞭一種基于空間定位的模糊C均值聚類方法( SPFCM )對目標進行分割。傳統的模糊C均值聚類法存在以下缺點:一是需要預先穫得目標分類數量,自適應性較差;二是對空間信息不敏感,導緻目標輪廓不完整以及錯誤分類。針對上述缺陷,文中對傳統算法進行瞭改進,引入瞭初定位的概唸,首先利用最大類間方差法(Otsu法)和數學形態學工具對子目標進行初步定位,再將其形心方位信息和灰度信息融閤到聚類過程中,以較短的迭代過程實現不同目標的歸類。實驗結果證明基于空間定位的模糊C均值聚類法可以完整、有效地對距離選通激光圖像進行提取分割,處理時間優于傳統FCM。
침대거리선통격광성상대비도저、조도불균、도상모호적특점,제출료일충기우공간정위적모호C균치취류방법( SPFCM )대목표진행분할。전통적모호C균치취류법존재이하결점:일시수요예선획득목표분류수량,자괄응성교차;이시대공간신식불민감,도치목표륜곽불완정이급착오분류。침대상술결함,문중대전통산법진행료개진,인입료초정위적개념,수선이용최대류간방차법(Otsu법)화수학형태학공구대자목표진행초보정위,재장기형심방위신식화회도신식융합도취류과정중,이교단적질대과정실현불동목표적귀류。실험결과증명기우공간정위적모호C균치취류법가이완정、유효지대거리선통격광도상진행제취분할,처리시간우우전통FCM。
A fuzzy C- means algorithm based on spatia l positioning was proposed to do the segmentation for range-gated image, which had the feature of low contrast, uneven illumination, and blurring. Object extraction is essential in image processing, providing the basic and necessary information for other methods. Traditional FCM algorithm needs the number of classes to cluster the data, which limits its adaptability. It also lacks in sensitivity of spatial information, resulting in misclassification as well as incomplete extraction of objects. For the above defects, the traditional algorithm was improved by pre-positioning. Firstly, median filter, Otsu method, and mathematical morphology method were applied to do the initial segmentation, obtaining the centroid and grayscale information of all targets, which took very short time. Then both of the centroid and grayscale information were used in clustering process, accomplishing the classification with fewer iterations and less time consuming than traditional FCM. Experiments indicate that the the Spatial Positioning FCM (SPFCM) is effective in segmentation of range-gated image, the targets can be extracted more completely and faster than traditional FCM algorithm. This new method can be applied to navigation, tracking and surveillance with range-gated imaging system.