<p>Difficulty depends on what you really want to classify, i.e. what exactly your data base of images is made ok.
For simple hand-drawn or computer art, I would think of just looking the color histogram (but for complex art with gradients; but still these gradients are likely to induce a very smooth colormap).</p>

<p>At the other extreme, distinguishing realistic computer graphics image from reality is probably impossible.</p>

CC BY-SA 3.0
2016-03-12T00:13:16.267Z
2016-03-12T00:13:16.267Z
Fabrice NEYRET
<p>Can an algorithm be derived to classify digital images according to how they were generated, i.e. the classes would be:</p>

<ul>
<li>Real-world photograph captured with an actual camera.</li>
<li>A Computer-Generated realistic scene.</li>
<li>A hand-drawn image or a painting.</li>
</ul>

<p>Could perhaps a Machine Learning approach, geared towards analyzing statistics of the signal provide sufficient insight on the problem ?
In that case, is there any known implementation of such algorithm publicly available ?</p>

CC BY-SA 3.0
2016-03-12T00:10:26.250Z
Putting online and use the google image advanced search ? :-p ( beside kidding, they might have publish (white) papers on that ).
Fabrice NEYRET
CC BY-SA 3.0
2016-03-12T11:25:11.537Z
Questions asking us to recommend or find a book, tool, software, tutorial or other off-site resource are off-topic as they tend to attract opinionated answers and spam. Instead, describe your problem or need and the steps, if any, you've taken to solve it.
trichoplax is on Codidact now
CC BY-SA 3.0
2016-03-12T11:28:02.647Z
As it stands, this question does not specify what types of images will need to be considered, so I am closing as unclear. The question may be reopened if it can be edited to clarify what types of non-photographic images will be presented, and to request an algorithm rather than an off site resource recommendation.
trichoplax is on Codidact now
CC BY-SA 3.0
2016-03-12T11:29:43.333Z
See also [What topics can I ask about here?](http://computergraphics.stackexchange.com/help/on-topic)
trichoplax is on Codidact now
CC BY-SA 4.0
2020-09-13T11:02:44.650Z
I would expect the histogram of real-world image to be a lot more noisy and chaotic that CG generated or CG-painted ( If image textures are not used ).
Of course, it's a pretty coarse criterion.
Fabrice NEYRET
<algorithm>
Separating photos from other images algorithmically?
Diova Eid
# Separating photos from other images algorithmically?

(Asked by: username_0 on 2016-03-11)

Can an algorithm be derived to classify digital images according to how they were generated, i.e. the classes would be:

* Real-world photograph captured with an actual camera.
* A Computer-Generated realistic scene.
* A hand-drawn image or a painting.

Could perhaps a Machine Learning approach, geared towards analyzing statistics of the signal provide sufficient insight on the problem ?
In that case, is there any known implementation of such algorithm publicly available ?

**Tags:** algorithm

> **Comments:**
> **username_1**: Putting online and use the google image advanced search ? :-p ( beside kidding, they might have publish (white) papers on that ).  
> **username_2**: Questions asking us to recommend or find a book, tool, software, tutorial or other off-site resource are off-topic as they tend to attract opinionated answers and spam. Instead, describe your problem or need and the steps, if any, you've taken to solve it.  
> **username_2**: As it stands, this question does not specify what types of images will need to be considered, so I am closing as unclear. The question may be reopened if it can be edited to clarify what types of non-photographic images will be presented, and to request an algorithm rather than an off site resource recommendation.  
> **username_2**: See also [What topics can I ask about here?](http://computergraphics.stackexchange.com/help/on-topic)  
> **username_1**: I would expect the histogram of real-world image to be a lot more noisy and chaotic that CG generated or CG-painted ( If image textures are not used ). Of course, it's a pretty coarse criterion.  

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## 1 answers

### Answer by username_1 on 2016-03-12. Score: 0

Difficulty depends on what you really want to classify, i.e. what exactly your data base of images is made ok.
For simple hand-drawn or computer art, I would think of just looking the color histogram (but for complex art with gradients; but still these gradients are likely to induce a very smooth colormap).

At the other extreme, distinguishing realistic computer graphics image from reality is probably impossible.


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