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Is there any way to figure out the pattern from an image?
I need it so that I could create a smaller image from it to repeat so that I could have a background pattern.
p.s: Don't mind the 2 different colors, I just need the almost transparent lines pattern figured out.
Here's a white and black repeating version of the pattern.
What did I do?
Copied some of the top portion of your image
Pasted it into a mask on a solid white layer
Added a photo under the layer to simulate the finished result
Inverted the mask
Adjusted the levels on the mask until I got an effect that was similar to your example
Cropped the image down to one pattern so it would be repeatable
Hit CMD CNTRL SHIFT S to save for web and saved it as a 24-bit PNG
Then inverted the white layer to black and saved for web again.
Does that seem to be what you were looking for?
I would use levels to get it to almost black & white.
Use sliders to get the lightest grey as light as possible
use the highlight/Shadow eyedropers within the levels palette to get it even closer
Use threshold to get it the rest of the way.
Take a look at the image below to see if what I described is what you are wanting.
Related
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How can I detect QR codes when processing the pixels of an image?
The image might be pixelated (low-fidelity), noisy (missing or extra pixels in a line), blurry (antialiasing), or be at an angle (image skew). Simply looping through the pixels seems like it would require some sort of line detection and then you could figure out a good calculate of the number of expected blocks between the three (or four) different corners.
You will need to use an image processing library to detect QRCodes. I’ve used go-zxing in the past which is 100% native go.
You will need to be familiar with the go image package that’s part of the standard library.
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I'm using Windows and I can't figure out how to batch insert images over a particular background image.
Here's what I'm trying to do:
https://imgur.com/bD32uVv
Here's the background image alone (1280x390):
https://imgur.com/gpBuFJG
Here's the folder with the several hundreds of images I would like to combine (each file is much larger so must fit in height with the same aspect ratio):
https://imgur.com/c8SXnOn
Any help would be greatly appreciated (I am using Windows).
The command for resizing a single foreground image to 360px high and compositing in the bottom-left of a background image will be something like:
magick FOREGROUND.PNG -resize x360 BACKGROUND.PNG +swap -gravity southwest -composite RESULT.PNG
Experiment with that, then follow #Mofi 's fine advice about looking up the documentation about FOR loops.
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I'm working on a project which involves detecting the red blood cells in the blood. RBCs in the blood are never perfectly circular (usually almost eliptical) and they often overlap.
I've searched and found a number of algorithms, but most work for circles only. However, in my case it needs to work for blood from patients with sickle cell disease, where the RBCs are elongated or sickle-shaped. For reference here is an example source image.
Can you suggest an algorithm or approach to solve this problem?
Any help would be greatly appreciated.
As mentioned in the comments, this question is really too broad to answer completely. However, I can give you some pointers in how to address this.
For starters, get yourself the MATLAB Image Processing toolbox.
"Identify red blood cells" is a deceptively simple-sounding task. The first step with any project like this is to figure out what exactly you want to achieve, then start breaking it down into steps of how you will achieve that. Finally, there is the experimental-developmental stage where you try and implement your plan (realise what is wrong with it, then try again).
Cell counting normally uses circularity to identify cells, but that's not possible here because you state you want to identify sickle cells. The other main characteristics distinguishing RBCs from other cells is the colour and size. The colour is more absolute, so start with that. Then think about size. This is a good tutorial on the process of identifying cells although it is in Python the principle is the same.
So we have:
Apply a filter to your image, either isolating the red channel (RGB) or something more complex. Make it monochrome (we don't need colour data).
Smooth the image (e.g. gaussian filter) to reduce the noise and artefacts
Find regional maxima which are (hopefully!) in the center of cells
Label the regional maxima (this should give you the number of cells)
Watershed to find the whole cells an measure size
Hopefully that is enough to get you started!
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I am working on detection of 2d data matrix but there is a problem in detection because barcode changes its design in each product so how to detect it? can anybody help me ?
The specification of datamatrix is designed to be identified. You need to look at the code the way it is intended to be looked at. Where I'd start is that the code has a quiet zone and an "L" pattern. That is what you are looking for.
How you go about doing this depends a lot on the general parameters of the image.
The first consideration is lighting and contrast. Can you depend on having a fixed midpoint, where everthing lighter is called white and everything darker black? Or will a simple histogram give a usable midpoint? Or do shadows and uneven lighting cause a value to be called black on the sunny side of the image and the same tone white on the shadow side of an image? On a flatbed scanner it is easy to depend on good contrast, but camera phone photos are more problematic.
The next consideration is size and resolution. For a camera phone application, it is expected that in a low resolution image, a high percentage of the image will contain the barcode, while a scanner may have a lot of image and a little amount of barcode data which needs to be searched for.
Finally comes presentation. Will the barcode appear in 360 degrees of rotation? Will it be flat and level or can it be be skewed, curled and angled? Is there any concern about lens distortion?
Once you can answer the considerations, it should point to what you need to do to identify the barcode. Datamatrix has clocking marks which enable distorted codes to be read, but it is a lot more work to define distortion, so if it is not needed, you wouldn't do it.
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I have this larger image: http://imgur.com/henxc that I need to create a smaller tile of to repeat as a background. However I'm having difficulty knowing what part I need to crop. Can someone please explain how to make this into a small piece that will tile? Is there a technique in Photoshop to make this easier maybe?
You can test if an image will "tile" by cutting it in half (copy half to another layer) and moving the left half to the right side and vice versa. Then you will see how the edges of the tile line up and can make adjustments. You can move one half over the other until they match up, mark them, and use that mark as the edge of the tile. Then repeat the process vertically.
This tut explains it better than I can (and with pictures) starting at step 5.
You should use the offset filter. You need to find the value which is exactly half of your image and enter for both of the numebrs. To get to it go to Filter > Other > Offset.