__2017-12-11 如一模式识别研究

如一模式识别研究

基本数学知识>>Opencv Python版学习笔记(一)图像直方图

转自http://blog.csdn.net/gjy095/article/details/9192299

之前接触c++版的Opencv一般都是用到什么就去找什么,最近安装了Python的Opencv,脚本语言就是有它的好处,直接运行就能看到好多例程:

今天看的是一个初级图像处理只是,颜色直方图,直接引用的Python版Opencv例程,需要注释的地方都加了说明

这个例子分别展示了3通道颜色直方图、灰度图像直方图、灰度直方图均衡化(也就是将直方图均匀开来,能够达到提升图像局部对比度的效果)后的直方图以及图像归一化后的直方图

[python] view plaincopy

import cv2

import numpy as np

bins = np.arange(256).reshape(256,1)

def hist_curve(im):

h = np.zeros((300,256,3))

if len(im.shape) == 2:#判断如果为灰度图像用白色线画,所以这里color赋值为白色

color = [(255,255,255)]

elif im.shape[2] == 3:#判断如果为彩色图像,分三个通道分别计算直方图

color = [ (255,0,0),(0,255,0),(0,0,255) ]

for ch, col in enumerate(color):#循环遍历3个通道,每次循环对划线进行颜色赋值,已达到清晰表示

hist_item = cv2.calcHist([im],[ch],None,[256],[0,255])#直方图计算[ch]为通道

cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)#直方图归一化

hist=np.int32(np.around(hist_item))#将归一化的直方图取整

pts = np.int32(np.column_stack((bins,hist)))#将bins列与直方图列合并

cv2.polylines(h,[pts],False,col)#通过构造得到的线pts在h上画出直方图曲线

y=np.flipud(h)#由于图是倒着的,将矩阵头尾对调

return y

def hist_lines(im):

h = np.zeros((300,256,3))

if len(im.shape)!=2:

print "hist_lines applicable only for grayscale images"

#print "so converting image to grayscale for representation"

im = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)#如果图片不是灰度图转为灰度图

hist_item = cv2.calcHist([im],[0],None,[256],[0,255])

cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)

hist=np.int32(np.around(hist_item))

for x,y in enumerate(hist):

cv2.line(h,(x,0),(x,y),(255,255,255))#以每个bin的累积高度作为纵坐标bin作为横坐标画垂直的线来表示直方图

#y = np.flipud(h)

return h

if __name__=='__main__':

import sys

if len(sys.argv)>1:

im = cv2.imread(sys.argv[1])

else :

im = cv2.imread('E:/lena.jpg')

print "usage : python hist.py "

gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)

print ''''' Histogram plotting \n

Keymap :\n

a - show histogram for color image in curve mode \n

b - show histogram in bin mode \n

c - show equalized histogram (always in bin mode) \n

d - show histogram for color image in curve mode \n

e - show histogram for a normalized image in curve mode \n

Esc - exit \n

'''

cv2.imshow('image',im)

while True:

k = cv2.waitKey(0)&0xFF

if k == ord('a'):

curve = hist_curve(im)

cv2.imshow('histogram',curve)

cv2.imshow('image',im)

print 'a'

elif k == ord('b'):

print 'b'

lines = hist_lines(im)

cv2.imshow('histogram',lines)

cv2.imshow('image',gray)

elif k == ord('c'):

print 'c'

equ = cv2.equalizeHist(gray)#直方图标准化

lines = hist_lines(equ)

cv2.imshow('histogram',lines)

cv2.imshow('image',equ)

elif k == ord('d'):

print 'd'

curve = hist_curve(gray)

cv2.imshow('histogram',curve)

cv2.imshow('image',gray)

elif k == ord('e'):

print 'e'

norm = cv2.normalize(gray,alpha = 0,beta = 255,norm_type = cv2.NORM_MINMAX)#灰度图归一化

lines = hist_lines(norm)

cv2.imshow('histogram',lines)

cv2.imshow('image',norm)

elif k == 27:

print 'ESC'

cv2.destroyAllWindows()

break

cv2.destroyAllWindows()

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