视觉/图像重磅干货，第一时间送达!
导 读
本文主要介绍Halcon转OpenCV实例--保险丝颜色识别(附源码)。
实例来源
实例来源于Halcon例程color_fuses.hdev--classify fuses by color
下面是Halcon实例代码和实现效果：
代码语言：javascript复制* color_fuses.hdev: classify fuses by color
dev_update_window ('off')
* ****
* step: set up fuse properties and hue ranges
* ****
FuseColors := ['Orange','Red','Blue','Yellow','Green']
FuseTypes := [5,10,15,20,30]
* HueRanges: Orange 10-30, Red 0-10...
HueRanges := [10,30,0,10,125,162,30,64,96,128]
Count := 0
dev_close_window ()
dev_open_window (0, 0, 800, 600, 'black', WH)
while (Count <= 4)
* ****
* step: acquire image
* ****
read_image (Image, 'color/color_fuses_0' Count)
dev_display (Image)
set_tposition (WH, 12, 512)
write_string (WH, 'color/color_fuses0' Count '.png')
* ****
* step: extract saturated hues
* ****
decompose3 (Image, Red, Green, Blue)
trans_from_rgb (Red, Green, Blue, Hue, Saturation, Intensity, 'hsv')
threshold (Saturation, Saturated, 60, 255)
reduce_domain (Hue, Saturated, HueSaturated)
for Fuse := 0 to |FuseTypes| - 1 by 1
* ****
* step: classify specific fuse
* ****
threshold (HueSaturated, CurrentFuse, HueRanges[Fuse * 2], HueRanges[Fuse * 2 1])
connection (CurrentFuse, CurrentFuseConn)
fill_up (CurrentFuseConn, CurrentFuseFill)
select_shape (CurrentFuseFill, CurrentFuseSel, 'area', 'and', 6000, 20000)
area_center (CurrentFuseSel, FuseArea, Row1, Column1)
dev_set_color ('magenta')
for i := 0 to |FuseArea| - 1 by 1
set_tposition (WH, Row1[i], Column1[i])
write_string (WH, FuseColors[Fuse] ' ' FuseTypes[Fuse] ' Ampere')
endfor
set_tposition (WH, 24 * (Fuse 1), 12)
dev_set_color ('slate blue')
write_string (WH, FuseColors[Fuse] ' Fuses: ' |FuseArea|)
endfor
stop ()
Count := Count 1
endwhile
dev_update_window ('on')
实现思路也比较简单，先将图像转到HSV颜色空间，然后分离S通道做阈值(60~255)，再分离H通道根据不同颜色的H范围来判定颜色。
OpenCV实现步骤与代码
测试图：
实现步骤：
【1】图像转到HSV颜色空间
【2】通道分离, 分离出H, S, V通道
【3】S通道做二值化(60~255)，然后通过轮廓查找提取每个保险丝的ROI
【4】对每个ROI做颜色判断：通过判断H通道特定范围内的像素数量
实现代码与测试效果：
代码语言：javascript复制#公众号：OpenCV与AI深度学习
import numpy as np
import cv2
FuseColors = ['Orange','Red','Blue','Yellow','Green']
def check_color(ROI):
index = 0
#判断是否为红色
_,thresRL = cv2.threshold(ROI,0,255,cv2.THRESH_BINARY)
_,thresRH = cv2.threshold(ROI,10,255,cv2.THRESH_BINARY)
thresRed = thresRL - thresRH
numRed = cv2.countNonZero(thresRed)
#cv2.imshow('thresRed',thresRed)
#判断是否为橙色
_,thresOL = cv2.threshold(ROI,5,255,cv2.THRESH_BINARY)
_,thresOH = cv2.threshold(ROI,25,255,cv2.THRESH_BINARY)
thresOrange = thresOL - thresOH
numOrange = cv2.countNonZero(thresOrange)
#cv2.imshow('thresOrange',thresOrange)
#判断是否为蓝色
_,thresBL = cv2.threshold(ROI,90,255,cv2.THRESH_BINARY)
_,thresBH = cv2.threshold(ROI,110,255,cv2.THRESH_BINARY)
thresBlue = thresBL - thresBH
numBlue = cv2.countNonZero(thresBlue)
#cv2.imshow('thresBlue',thresBlue)
#判断是否为黄色
_,thresYL = cv2.threshold(ROI,25,255,cv2.THRESH_BINARY)
_,thresYH = cv2.threshold(ROI,65,255,cv2.THRESH_BINARY)
thresYellow = thresYL - thresYH
numYellow = cv2.countNonZero(thresYellow)
#cv2.imshow('thresYellow',thresYellow)
#判断是否为绿色
_,thresGL = cv2.threshold(ROI,65,255,cv2.THRESH_BINARY)
_,thresGH = cv2.threshold(ROI,90,255,cv2.THRESH_BINARY)
thresGreen = thresGL - thresGH
numGreen = cv2.countNonZero(thresGreen)
#cv2.imshow('thresGreen',thresGreen)
max_val = max(numRed, numBlue,numYellow, numGreen,numOrange)
#print(max_val)
if max_val == numOrange:
index = 0
elif max_val == numRed:
index = 1
elif max_val == numBlue:
index = 2
elif max_val == numYellow:
index = 3
else:
index = 4
return index
img=cv2.imread("./color_fuses_01.png")
cv2.imshow('src',img)
rows,cols,channel = img.shape
hsv_img=cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
hImg,sImg,vImg=cv2.split(hsv_img)
_,thres = cv2.threshold(sImg,60,255,cv2.THRESH_BINARY)
cv2.imshow('thres',thres)
cv2.imshow('hImg',hImg)
cv2.imwrite('h.jpg',hImg)
#cv2.waitKey()
contours,hierarchy = cv2.findContours(thres, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for i in range(0,len(contours)):
rect = cv2.minAreaRect(contours[i])
box = cv2.boxPoints(rect)
box = np.int0(box)
width = rect[1][0]
height = rect[1][1]
if width < 100 or height < 100:
continue
(x, y, w, h) = cv2.boundingRect(contours[i])
ROI = hImg[y:y h,x:x w]
index = check_color(ROI)
center = (int(rect[0][0]),int(rect[0][1]))
radius = (int)(max(width,height)/2 20)
if index == 0:
cv2.circle(img,center,radius,(0,128,255),3)
#img = cv2.drawContours(img,[box],0,(0,128,255),3)
cv2.putText(img,FuseColors[index],center,0,1.2,(255,255,0),2)
elif index == 1:
cv2.circle(img,center,radius,(0,0,255),3)
#img = cv2.drawContours(img,[box],0,(0,0,255),3)
cv2.putText(img,FuseColors[index],center,0,1.2,(0,255,0),2)
elif index == 2:
cv2.circle(img,center,radius,(255,255,0),3)
#img = cv2.drawContours(img,[box],0,(255,255,0),3)
cv2.putText(img,FuseColors[index],center,0,1.2,(255,0,255),2)
elif index == 3:
cv2.circle(img,center,radius,(0,255,255),3)
#img = cv2.drawContours(img,[box],0,(0,255,255),3)
cv2.putText(img,FuseColors[index],center,0,1.2,(0,255,128),2)
elif index == 4:
cv2.circle(img,center,radius,(0,255,0),3)
#img = cv2.drawContours(img,[box],0,(0,255,0),3)
cv2.putText(img,FuseColors[index],center,0,1.2,(0,0,255),2)
cv2.imshow('result',img)
cv2.waitKey()
cv2.destroyAllWindows()
