当我们想比较两张图片相似度的时候,可以使用这一节提到的技术
关于这两种技术的原理可以参考我上面贴的链接,下面是示例的代码:
0x01. 绘制直方图
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 |
import cv2.cv as cv def drawGraph(ar,im, size): #Draw the histogram on the image minV, maxV, minloc, maxloc = cv.MinMaxLoc(ar) #Get the min and max value hpt = 0.9 * histsize for i in range(size): intensity = ar[i] * hpt / maxV #Calculate the intensity to make enter in the image cv.Line(im, (i,size), (i,int(size-intensity)),cv.Scalar(255,255,255)) #Draw the line i += 1 #---- Gray image orig = cv.LoadImage("img/lena.jpg", cv.CV_8U) histsize = 256 #Because we are working on grayscale pictures which values within 0-255 hist = cv.CreateHist([histsize], cv.CV_HIST_ARRAY, [[0,histsize]], 1) cv.CalcHist([orig], hist) #Calculate histogram for the given grayscale picture histImg = cv.CreateMat(histsize, histsize, cv.CV_8U) #Image that will contain the graph of the repartition of values drawGraph(hist.bins, histImg, histsize) cv.ShowImage("Original Image", orig) cv.ShowImage("Original Histogram", histImg) #--------------------- #---- Equalized image imEq = cv.CloneImage(orig) cv.EqualizeHist(imEq, imEq) #Equlize the original image histEq = cv.CreateHist([histsize], cv.CV_HIST_ARRAY, [[0,histsize]], 1) cv.CalcHist([imEq], histEq) #Calculate histogram for the given grayscale picture eqImg = cv.CreateMat(histsize, histsize, cv.CV_8U) #Image that will contain the graph of the repartition of values drawGraph(histEq.bins, eqImg, histsize) cv.ShowImage("Image Equalized", imEq) cv.ShowImage("Equalized HIstogram", eqImg) #-------------------------------- cv.WaitKey(0) |
0x02. 反向投影
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 |
import cv2.cv as cv im = cv.LoadImage("img/lena.jpg", cv.CV_8U) cv.SetImageROI(im, (1, 1,30,30)) histsize = 256 #Because we are working on grayscale pictures hist = cv.CreateHist([histsize], cv.CV_HIST_ARRAY, [[0,histsize]], 1) cv.CalcHist([im], hist) cv.NormalizeHist(hist,1) # The factor rescale values by multiplying values by the factor _,max_value,_,_ = cv.GetMinMaxHistValue(hist) if max_value == 0: max_value = 1.0 cv.NormalizeHist(hist,256/max_value) cv.ResetImageROI(im) res = cv.CreateMat(im.height, im.width, cv.CV_8U) cv.CalcBackProject([im], res, hist) cv.Rectangle(im, (1,1), (30,30), (0,0,255), 2, cv.CV_FILLED) cv.ShowImage("Original Image", im) cv.ShowImage("BackProjected", res) cv.WaitKey(0) |