<p>First simple thresholding is usually not a good idea. However, if you want to do that, I suggest to also consider other <a href="https://en.wikipedia.org/wiki/Color_space" rel="nofollow noreferrer">color spaces</a>. In your case, <a href="https://en.wikipedia.org/wiki/HSL_and_HSV" rel="nofollow noreferrer">HSV</a> might be a better choice; You can convert your image into HSV-image then you can define a range on Hue channel to select yellow.</p>

<p>Also, take a look at <a href="http://homepages.inf.ed.ac.uk/rbf/HIPR2/adpthrsh.htm" rel="nofollow noreferrer">this article</a>; it is about implementing <strong>Adaptive Thresholding</strong>.</p>

CC BY-SA 3.0
2017-08-22T05:39:09.370Z
2017-08-22T05:39:09.370Z
Aref
<p>I have a series of images obtained from a microscope as follows</p>

<p><a href="https://i.sstatic.net/qCMPx.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/qCMPx.jpg" alt="Time step 3"></a></p>

<p>I need to create a series of filters that would isolate the centre section    on the yellow droplet.(This is highlighted by the bright yellow circle area), and remove all the noise and other pictures.
<a href="https://i.sstatic.net/epfyH.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/epfyH.png" alt="enter image description here"></a>
I tried using just RGB  channel threshold but its not working. Also ambient light may also change so I am not getting a consistent output. Can anyone provide a MWE for the workflow of the filter required in MATLAB to achieve this?</p>

CC BY-SA 3.0
2017-08-30T06:34:34.017Z
Did you produce the black dot from the yellow dot image using thresholding? Looks pretty spot on to me? Or is that what you want to achieve? You could consider some sort of region growing technique? Like active contours?
Andrew Wilson
CC BY-SA 3.0
2017-08-30T06:54:03.630Z
I achieved this by manual thresholding-median filtering-noise reduction on ImageJ...I have thousands of these images and would like to get a generalized image processing procedure to implement a batch algorithm
Fowaz Ikram
CC BY-SA 3.0
2017-08-30T08:14:14.963Z
Theres a lot of papers on automatically thresholding images. A quick look at the images histogram should make it obvious where you should threshold.
Andrew Wilson
<image-processing><matlab>
Appropriate filter steps for resolving a droplet pixel
Fowaz Ikram
# Appropriate filter steps for resolving a droplet pixel

(Asked by: username_0 on 2017-08-22)

I have a series of images obtained from a microscope as follows

[![Time step 3](https://i.sstatic.net/qCMPx.jpg)](https://i.sstatic.net/qCMPx.jpg)

I need to create a series of filters that would isolate the centre section on the yellow droplet.(This is highlighted by the bright yellow circle area), and remove all the noise and other pictures.
[![enter image description here](https://i.sstatic.net/epfyH.png)](https://i.sstatic.net/epfyH.png)
I tried using just RGB channel threshold but its not working. Also ambient light may also change so I am not getting a consistent output. Can anyone provide a MWE for the workflow of the filter required in MATLAB to achieve this?

**Tags:** image-processing, matlab

> **Comments:**
> **username_1**: Did you produce the black dot from the yellow dot image using thresholding? Looks pretty spot on to me? Or is that what you want to achieve? You could consider some sort of region growing technique? Like active contours?  
> **username_0**: I achieved this by manual thresholding-median filtering-noise reduction on ImageJ...I have thousands of these images and would like to get a generalized image processing procedure to implement a batch algorithm  
> **username_1**: Theres a lot of papers on automatically thresholding images. A quick look at the images histogram should make it obvious where you should threshold.  

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## 1 answers

### Answer by username_2 on 2017-08-22. Score: 1 | Accepted answer

First simple thresholding is usually not a good idea. However, if you want to do that, I suggest to also consider other [color spaces](https://en.wikipedia.org/wiki/Color_space). In your case, [HSV](https://en.wikipedia.org/wiki/HSL_and_HSV) might be a better choice; You can convert your image into HSV-image then you can define a range on Hue channel to select yellow.

Also, take a look at [this article](http://homepages.inf.ed.ac.uk/rbf/HIPR2/adpthrsh.htm); it is about implementing **Adaptive Thresholding**.


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