西安工程大学学报
西安工程大學學報
서안공정대학학보
JOURNAL OF XI'AN POLYTECHNIC UNIVERSITY
2014年
6期
745-749
,共5页
拓小明%李云红%刘旭%曹浏%霍可%田冀达%陈航
拓小明%李雲紅%劉旭%曹瀏%霍可%田冀達%陳航
탁소명%리운홍%류욱%조류%곽가%전기체%진항
Canny算子%边缘检测%图像增强%高斯分布%概率密度%最小均方误差
Canny算子%邊緣檢測%圖像增彊%高斯分佈%概率密度%最小均方誤差
Canny산자%변연검측%도상증강%고사분포%개솔밀도%최소균방오차
Canny operator%edge detection%image enhancement%Gaussian distribution%probability den-sity%minimum mean square error
针对传统Canny算子阈值选择困难的问题,提出一种基于最小均方误差计算高低阈值的方法。首先对采集到的图像进行增强处理,提高对比度,然后把图像中的灰度作为模式特征。假定各个模式中灰度的随机变量是独立分布的,根据增强后图像的目标和背景模式服从高斯分布的特征,通过两个概率密度函数的解析式,从而得到Canny算子的高、低阈值。最后,将边缘检测算法与Canny算子提取边缘算法、最小均方误差法提取边缘算法进行相互比较,结果表明,采用本文的算法提取图像的边缘更加清晰有效。
針對傳統Canny算子閾值選擇睏難的問題,提齣一種基于最小均方誤差計算高低閾值的方法。首先對採集到的圖像進行增彊處理,提高對比度,然後把圖像中的灰度作為模式特徵。假定各箇模式中灰度的隨機變量是獨立分佈的,根據增彊後圖像的目標和揹景模式服從高斯分佈的特徵,通過兩箇概率密度函數的解析式,從而得到Canny算子的高、低閾值。最後,將邊緣檢測算法與Canny算子提取邊緣算法、最小均方誤差法提取邊緣算法進行相互比較,結果錶明,採用本文的算法提取圖像的邊緣更加清晰有效。
침대전통Canny산자역치선택곤난적문제,제출일충기우최소균방오차계산고저역치적방법。수선대채집도적도상진행증강처리,제고대비도,연후파도상중적회도작위모식특정。가정각개모식중회도적수궤변량시독립분포적,근거증강후도상적목표화배경모식복종고사분포적특정,통과량개개솔밀도함수적해석식,종이득도Canny산자적고、저역치。최후,장변연검측산법여Canny산자제취변연산법、최소균방오차법제취변연산법진행상호비교,결과표명,채용본문적산법제취도상적변연경가청석유효。
In view of the threshold selection difficulty of traditional Canny operator ,a method to calculate high and low threshold based on minimum mean square error w as proposed .First of all ,in order to im‐prove the contrast ratio ,the collected images was enhanced .And then the gray degree as characterized model was selected ,assuming the random variable of each pattern of gray was independent distribution . Since the enhanced images of target and backgrounds obeyed the Gaussian distribution characteristic , high and low threshold could be received by two analytic formula of probability density function .Finally , compared with the method of Canny operator and minimum mean square error ,the results showed that the proposed method could extract the edge of information more clearly and effectively .