Tracking White Color Using Python Opencv - Stack Overflow

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Learn more about Labs Tracking white color using python opencv Ask Question Asked 10 years, 8 months ago Modified 5 years, 1 month ago Viewed 100k times 37

I would like to track white color using webcam and python opencv. I already have the code to track blue color.

_, frame = cap.read() hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) # define range of blue color in HSV lower_blue = np.array([110,100,100]) upper_blue = np.array([130,255,255]) #How to define this range for white color # Threshold the HSV image to get only blue colors mask = cv2.inRange(hsv, lower_blue, upper_blue) # Bitwise-AND mask and original image res = cv2.bitwise_and(frame,frame, mask= mask) cv2.imshow('frame',frame) cv2.imshow('mask',mask) cv2.imshow('res',res)

what values should I give as lower bound and upper bound to track white color!!?? I tried changing values and I got other colors but no luck with the white color!!!

is that HSV values or BGR values specified as lower and upper bounds???

PS : I must get the last result as a binary image for further processing!!

Please help me !!!

• python
• opencv
• computer-vision
• hsv
• color-tracking

Share Improve this question Follow edited May 24, 2014 at 12:50 Alessandro Jacopson 18.6k1616 gold badges104104 silver badges155155 bronze badges asked Mar 23, 2014 at 7:23 user3429616user3429616 38111 gold badge44 silver badges88 bronze badges 1

• Just fixed my code so it now indeed produces low saturation and high value :) – Legat Commented Mar 23, 2014 at 9:12

Add a comment |

3 Answers 3

Sorted by: Reset to default Highest score (default) Trending (recent votes count more) Date modified (newest first) Date created (oldest first) 61

Let's take a look at HSV color space:

You need white, which is close to the center and rather high. Start with

sensitivity = 15 lower_white = np.array([0,0,255-sensitivity]) upper_white = np.array([255,sensitivity,255])

and then adjust the threshold to your needs.

You might also consider using HSL color space, which stands for Hue, Saturation, Lightness. Then you would only have to look at lightness for detecting white and recognizing other colors would stay easy. Both HSV and HSL keep similar colors close. Also HSL would probably prove more accurate for detecting white - here is why:

Share Improve this answer Follow edited Mar 23, 2014 at 9:24 answered Mar 23, 2014 at 8:01 LegatLegat 1,43933 gold badges1212 silver badges2020 bronze badges 3

• How to reduce the useless noise !!!! everythingis getting tracked when i use a webcam – user3429616 Commented Mar 23, 2014 at 9:13
• With new color components as well. You can set the thresholds higher. Let me edit the answer once more to clarify :) – Legat Commented Mar 23, 2014 at 9:16
• Ready. Used sensitivity instead of threshold. Lower sensitivity gives less noise. – Legat Commented Mar 23, 2014 at 9:24

Add a comment | 22

Here's an HSV color thresholder script to determine the lower and upper bounds using sliders

Results

Using this sample image

With these lower/upper thresholds

lower_white = np.array([0,0,168]) upper_white = np.array([172,111,255])

We get isolated white pixels (left) and the binary mask (right)

Here's the script, remember to change the input image path

import cv2 import sys import numpy as np def nothing(x): pass # Load in image image = cv2.imread('1.jpg') # Create a window cv2.namedWindow('image') # create trackbars for color change cv2.createTrackbar('HMin','image',0,179,nothing) # Hue is from 0-179 for Opencv cv2.createTrackbar('SMin','image',0,255,nothing) cv2.createTrackbar('VMin','image',0,255,nothing) cv2.createTrackbar('HMax','image',0,179,nothing) cv2.createTrackbar('SMax','image',0,255,nothing) cv2.createTrackbar('VMax','image',0,255,nothing) # Set default value for MAX HSV trackbars. cv2.setTrackbarPos('HMax', 'image', 179) cv2.setTrackbarPos('SMax', 'image', 255) cv2.setTrackbarPos('VMax', 'image', 255) # Initialize to check if HSV min/max value changes hMin = sMin = vMin = hMax = sMax = vMax = 0 phMin = psMin = pvMin = phMax = psMax = pvMax = 0 output = image wait_time = 33 while(1): # get current positions of all trackbars hMin = cv2.getTrackbarPos('HMin','image') sMin = cv2.getTrackbarPos('SMin','image') vMin = cv2.getTrackbarPos('VMin','image') hMax = cv2.getTrackbarPos('HMax','image') sMax = cv2.getTrackbarPos('SMax','image') vMax = cv2.getTrackbarPos('VMax','image') # Set minimum and max HSV values to display lower = np.array([hMin, sMin, vMin]) upper = np.array([hMax, sMax, vMax]) # Create HSV Image and threshold into a range. hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) mask = cv2.inRange(hsv, lower, upper) output = cv2.bitwise_and(image,image, mask= mask) # Print if there is a change in HSV value if( (phMin != hMin) | (psMin != sMin) | (pvMin != vMin) | (phMax != hMax) | (psMax != sMax) | (pvMax != vMax) ): print("(hMin = %d , sMin = %d, vMin = %d), (hMax = %d , sMax = %d, vMax = %d)" % (hMin , sMin , vMin, hMax, sMax , vMax)) phMin = hMin psMin = sMin pvMin = vMin phMax = hMax psMax = sMax pvMax = vMax # Display output image cv2.imshow('image',output) # Wait longer to prevent freeze for videos. if cv2.waitKey(wait_time) & 0xFF == ord('q'): break cv2.destroyAllWindows() Share Improve this answer Follow answered Oct 1, 2019 at 23:12 nathancynathancy 46.3k1515 gold badges131131 silver badges153153 bronze badges 0 Add a comment | 21

I wrote this for tracking white color :

import cv2 import numpy as np cap = cv2.VideoCapture(0) while(1): _, frame = cap.read() hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) # define range of white color in HSV # change it according to your need ! lower_white = np.array([0,0,0], dtype=np.uint8) upper_white = np.array([0,0,255], dtype=np.uint8) # Threshold the HSV image to get only white colors mask = cv2.inRange(hsv, lower_white, upper_white) # Bitwise-AND mask and original image res = cv2.bitwise_and(frame,frame, mask= mask) cv2.imshow('frame',frame) cv2.imshow('mask',mask) cv2.imshow('res',res) k = cv2.waitKey(5) & 0xFF if k == 27: break cv2.destroyAllWindows()

I tried to track the white screen of my phone and got this :

You can try changing the HSV values You might also try HSL color space as Legat said, it would be more accurate

Share Improve this answer Follow answered Mar 23, 2014 at 8:35 VipulVipul 4,14899 gold badges3434 silver badges5656 bronze badges Add a comment |

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