Python OpenCV處理圖像之圖像直方圖和反向投影

更新時(shí)間：2018年07月10日 17:13:04 作者：Leo

這篇文章主要為大家詳細(xì)介紹了Python OpenCV處理圖像之圖像直方圖和反向投影，具有一定的參考價(jià)值，感興趣的小伙伴們可以參考一下

本文實(shí)例為大家分享了Python OpenCV圖像直方圖和反向投影的具體代碼，供大家參考，具體內(nèi)容如下

當(dāng)我們想比較兩張圖片相似度的時(shí)候，可以使用這一節(jié)提到的技術(shù)

直方圖對比

反向投影

關(guān)于這兩種技術(shù)的原理可以參考我上面貼的鏈接，下面是示例的代碼：

0x01. 繪制直方圖

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)

以上就是本文的全部內(nèi)容，希望對大家的學(xué)習(xí)有所幫助，也希望大家多多支持腳本之家。

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