我可能还没有完全理解直方图...但我想我可以得到一个二维的灰度图像,对吗?
一维很好:
from cv import *
import os, glob, sys
original = LoadImage('test.jpg')
gray = CreateImage(GetSize(original), IPL_DEPTH_8U, 1)
canny = CreateImage(GetSize(original), IPL_DEPTH_8U, 1)
NamedWindow('Circles', 1)
CvtColor(original, gray, CV_BGR2GRAY)
bins = 30
scale = 10
hist = CreateHist([bins], CV_HIST_ARRAY, [[0,256]], 1)
CalcHist([gray], hist)
hist_img = CreateImage([bins*scale,50], 8, 1)
Rectangle(hist_img, (0,0), (bins*scale,50), CV_RGB(255,255,255), -1)
(_, max_value, _, _) = GetMinMaxHistValue(hist)
for i in range(0,bins):
bin_val = QueryHistValue_1D(hist, i)
#print bin_val
norm = Round((bin_val/max_value)*50)
Rectangle(hist_img, (i*scale, 50), (i*scale+scale-1,50-norm), CV_RGB(0, 0, 0), CV_FILLED)
ShowImage('Circles', hist_img)
WaitKey(0)
但是当我打电话给CalcHist时,第二个人说他需要两架飞机或图像:
from cv import *
import os, glob, sys
original = LoadImage('test.jpg')
gray = CreateImage(GetSize(original), IPL_DEPTH_8U, 1)
NamedWindow('Circles', 1)
CvtColor(original, gray, CV_BGR2GRAY)
bins = 30
scale = 3
hist = CreateHist([bins,bins], CV_HIST_ARRAY, [[0,255], [0,255]], 1)
CalcHist([gray], hist)
hist_img = CreateImage([bins*scale,bins*scale], 8, 1)
#Rectangle(hist_img, (0,0), (bins*scale,50), CV_RGB(255,255,255), -1)
Zero(hist_img)
(_, max_value, _, _) = GetMinMaxHistValue(hist)
for h in range(0,bins):
for s in range(0,bins):
bin_val = QueryHistValue_2D(hist, h, s)
inte = Round(bin_val*255/max_value)
Rectangle(hist_img, (h*scale, s*scale), ((h+1)*scale-1,(s+1)*scale-1), CV_RGB(inte, inte, inte), CV_FILLED)
ShowImage('Circles', hist_img)
WaitKey(0)
此错误:
OpenCV Error: Bad argument (Unknown array type) in cvarrToMat, file /opt/local/var/macports/build/_opt_local_var_macports_sources_rsync.macports.org_release_ports_graphics_opencv/work/OpenCV-2.2.0/modules/core/src/matrix.cpp, line 641
Traceback (most recent call last):
File "hist2d.py", line 16, in <module>
CalcHist([gray], hist, 0)
cv.error: Unknown array type
如果我使用:
CalcHist([gray, gray], hist, 0)
它有效,但我得到了一个搞乱的直方图(对角线颜色,其余为黑色)
所以...有人可以启发我吗?
答案 0 :(得分:4)
灰度图像已经是二维直方图:像素的强度( a , b )是 a 定义的bin的值沿着x维度的em>和沿着y维度的 b 。通常,当人们谈到计算机视觉中的直方图时,人们会谈到histogram over intensity values。对于灰度图像,这是一维直方图,其中每个bin对应于一系列强度值,并且具有与强度落在该bin中的像素数对应的计数。
如果图像是多个通道,则高维直方图才有意义。例如,可以计算彩色图像上RGB值的三维直方图。调用CalcHist([gray, gray], hist, 0)
会产生对角线,因为第一个图像(gray
)中的每个像素都具有与第二个图像(gray
)中相应像素相同的值。这会在输出直方图中沿对角线填充所有区域。
另外,请注意多维直方图与三维一维直方图非常不同。
答案 1 :(得分:1)
bins = 10 # specify the number of bins
ranges = (10,255) % specify the top and bottom range of the bins. This truncates the image
hist = cv.CreateHist([bins], cv.CV_HIST_ARRAY, [ranges], 1) # create histograms
cv.CalcHist([gr], hist) # calculate the histograms for the image
(min_value, max_value, min_idx, max_idx) = cv.GetMinMaxHistValue(hist) # get the min and max values for the histogram
答案 2 :(得分:0)
更高暗淡。 hists 不仅 在 RGB-image-analysis中查看 - 这些只是强度嘶嘶声 - 而且还在特征提取中 < / strong>就像在GLCM(灰度共生矩阵,2D),形状上下文(昏暗。取决于算法)等。