It is quite hard to explain what I want in the title. I'll show what I need with an example or input/output. I have an image called 'image.jpg' that'll be an image with random strokes of different shades of black and dark-blackish gray on a white background and on one area it'll be a light grey background
I want to use python's opencv and maybe PIL if it's useful and crop the image so I'll only see the gray area. So after whatever code I'll do it'll look like this image here
That's it, appreciate all help here. I don't seem to know where to start here so I can't include whatever code I tried.
Related
I'd like to remove this sort of tv-like noise from a .jpg image in order to get a .png image with transparent background.
This is because I'll later need to overlay this picture over another one.
I've tried 1,
2,3, but all of them probably work only on black backgrounds.
I'm coding with Python and I thought OpenCV would help.
Do you have any idea? Thanks! :)
Given that the noise is nearly exclusively black and white (i.e. desaturated) whereas the fish is colour, I would convert to HSV colourspace and look to the Saturation channel for providing separation - the middle one in the row below:
I have an image of a map with black borders, and I would like to make them thicker with opencv on python. To be honest, I am quite new to image processing and really don't know how this task can be accomplished. I already opened the image with just one color channel, since it is black and white, but I really have no idea as of what to do next to be able to accomplish what I need.
Here is the image that I am talking about:
map
Thanks in advance
I am very new to OpenCV(and to StackOverflow). I'm writing a program with OpenCV which takes a picture with an object (i.e. pen(rice, phone) put on paper) and calculates what percent does the object make of the picture.
Problem I'm facing with is when I threshold image (tried adaptive and otsu) photo is a little bit shadow around edges:
Original image
Resulted picture
And here's my code:
import cv2
img = cv2.imread("image.png")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
b,g,r = cv2.split(img)
th, thresh = cv2.threshold(b, 100, 255, cv2.THRESH_BINARY|cv2.THRESH_OTSU)
cv2.imwrite("image_bl_wh.png", thresh)
Tried to blur and morphology, but couldn't do it.
How can I make my program count that black parts around the picture as background and is there more better and easier way to do it?
P.S. Sorry for my English grammar mistakes.
This is not a programmatic solution but when you do automatic visual inspection it is the first thing you should try: Improve your set-up. The image is simply darker around the edges so increasing the brightness when recording the images should help.
If that's not an option you could consider having an empty image for comparison. What you are trying to do is background segmentation and there are better ways than simple color thresholding they do however usually require at least one image of the background or multiple images.
If you want a software only solution you should try an edge detector combined with morphological operators.
I want to convert the picture into black and white image accurately where the seeds will be represented by white color and the background as black color. I would like to have it in python opencv code. Please help me out
I got good result for the above picture using the given code below. Now I have another picture for which thresholding doesn't seem to work. How can I tackle this problem. The output i got is in the following picture
also, there are some dents in the seeds, which the program takes it as the boundary of the seed which is not a good results like in the picture below. How can i make the program ignore dents. Is masking the seeds a good option in this case.
I converted the image from BGR color space to HSV color space.
Then I extracted the hue channel:
Then I performed threshold on it:
Note:
Whenever you face difficulty in certain areas try working in a different color space, the HSV color space being most prominent.
UPDATE:
Here is the code:
import cv2
import numpy as np
filename = 'seed.jpg'
img = cv2.imread(filename) #---Reading image file---
hsv_img = cv2.cvtColor(img,cv2.COLOR_BGR2HSV) #---Converting RGB image to HSV
hue, saturation, value, = cv2.split(hsv_img) #---Splitting HSV image to 3 channels---
blur = cv2.GaussianBlur(hue,(3,3),0) #---Blur to smooth the edges---
ret,th = cv2.threshold(blur, 38, 255, 0) #---Binary threshold---
cv2.imshow('th.jpg',th)
Now you can perform contour operations to highlight your regions of interest also. Try it out!! :)
ANOTHER UPDATE:
I found the contours higher than a certain constraint to get this:
There are countless ways for image segmentation.
The simplest one is a global threshold operation. If you want to know more on other methods you should read some books. Which I recommend anyway befor you do any further image processing. It doesn't make much sense to start image processing if you don't know the most basic tools.
Just to show you how this could be achieved:
I converted the image from RGB to HSB. I then applied separate global thresholds to the hue and brightness channels to get the best segmentation result for both images.
Both binary images were then combined using a pixelwise AND operation. I did this because both channels gave sub-optimal results, but their overlap was pretty good.
I also applied some morphological operators to clean up the results.
Of course you can just invert the image to get the desired black background...
Thresholds and the used channels of course depend on the image you have and what you want to achieve. This is a very case-specific process that can be dynamically adapted to a limited extend.
This could be followed by labling or whatever you need:
I am trying to paste many small grayscale images into a bigger one. All images are jpegs. The small images had been previously rotated, so they have black background. What I wanted to do is to paste them without a background color, in other words, I need the background color to be transparent.
Thank you for your suggestions,
to my knowledge, jpg does not support transparency, you probably want your output to be a png, and you will need to set the alpha channel to be nothing
http://www.talkgraphics.com/showthread.php?22385-How-do-I-make-jpeg-image-background-transparent