<p>How to develop a program that can sort images by similarity is similar to the problem of how to develop a program that can sort words by how similar they look.</p>

<p>For example:
"theory" is more similar to "teoryyy" than to "abc".</p>

<p>What determines similarity of two words or images are these factors:</p>

<ul>
<li><p>how many parts are common to both images</p></li>
<li><p>how many parts are new in either image</p></li>
<li><p>how many parts are missing in either image</p></li>
<li><p>how many parts are zoomed in/out or stretched.</p></li>
<li><p>how many parts are displaced</p></li>
</ul>

<p>There may be some other rules. By combining these rules you can explain how similarity recognition works. This is at the core of intelligence.</p>

CC BY-SA 4.0
2018-10-25T21:14:19.367Z
2018-10-25T21:14:19.367Z
Tone Škoda
<p>I am developing an image search engine. The engine is meant to retrieve wrist watches based on the input of the user. I am using SIFT descriptors to index the elements in the database and applying Euclidean distance to get the most similar watches. I feel like this type of descriptor is not the best since watches have a similar structure and shape. Right now, the average difference between the best and worst matches is not big enough (15%)</p>

<p>I've been thinking of adding colour to the descriptor, but I'd like to hear other suggestions.</p>

CC BY-SA 4.0
2018-12-25T20:52:43.690Z
Why are you using SIFT?  Have you tried deep learning?
Brian O'Donnell
<image-recognition><computer-vision><feature-selection>
What is a good descriptor for similar objects?
sosegon
# What is a good descriptor for similar objects?

(Asked by: username_0 on 2018-10-23)

I am developing an image search engine. The engine is meant to retrieve wrist watches based on the input of the user. I am using SIFT descriptors to index the elements in the database and applying Euclidean distance to get the most similar watches. I feel like this type of descriptor is not the best since watches have a similar structure and shape. Right now, the average difference between the best and worst matches is not big enough (15%)

I've been thinking of adding colour to the descriptor, but I'd like to hear other suggestions.

**Tags:** image-recognition, computer-vision, feature-selection

> **Comments:**
> **username_1**: Why are you using SIFT?  Have you tried deep learning?  

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## 1 answers

### Answer by username_2 on 2018-10-25. Score: 2

How to develop a program that can sort images by similarity is similar to the problem of how to develop a program that can sort words by how similar they look.

For example:
"theory" is more similar to "teoryyy" than to "abc".

What determines similarity of two words or images are these factors:

* how many parts are common to both images
* how many parts are new in either image
* how many parts are missing in either image
* how many parts are zoomed in/out or stretched.
* how many parts are displaced

There may be some other rules. By combining these rules you can explain how similarity recognition works. This is at the core of intelligence.


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