Python OpenCV处理图像之图像直方图和反向投影_Python

Python OpenCV处理图像之图像直方图和反向投影

2021-03-15 00:38Leo Python

这篇文章主要为大家详细介绍了Python OpenCV处理图像之图像直方图和反向投影，具有一定的参考价值，感兴趣的小伙伴们可以参考一下

本文实例为大家分享了Python OpenCV图像直方图和反向投影的具体代码，供大家参考，具体内容如下

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

直方图对比

反向投影

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

									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

									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)