<p>My aim is to classify types of cars (Sedans,SUV,Hatchbacks) and earlier I was using corner features for classification but it didn't work out very well so now I am trying Gabor features.<br/></p>

<p><a href="http://www.mathworks.in/matlabcentral/fileexchange/38844-gabor-image-features" rel="nofollow">code from here</a><br/></p>

<p>Now the features are extracted and suppose when I give an image as input then for 5 scales and 8 orientations I get 2 [1x40] matrices.</p>

<p><strong>1. 40 columns of squared Energy.</strong></p>

<p><strong>2. 40 colums of mean Amplitude.</strong></p>

<p>Problem is I want to use these two matrices for classification and I have about 230 images of 3 classes (SUV,sedan,hatchback).</p>

<p>I do not know how to create a [N x 230] matrix which can be taken as vInputs by the neural netowrk in matlab.(where N be the total features of one image).</p>

<p>My question:</p>

<ol>
<li><p>How to create a one dimensional image vector from the 2 [1x40] matrices for one image.(should I append the mean Amplitude to square energy matrix to get a [1x80] matrix or something else?)</p></li>
<li><p>Should I be using these gabor features for my purpose of classification in first place? if not then what?</p></li>
</ol>

<p>Thanks in advance</p>

CC BY-SA 3.0
2013-11-14T08:43:25.840Z
This question seems more suitable for [stats.se].
Kaveh
CC BY-SA 3.0
2013-11-16T13:56:52.490Z
Ok but I learnt from metastackoverflow that this site can also be useful....anyways I got my answer myself thanks :)
xor
<machine-learning><image-processing>
Making feature vector from Gabor filters for classification using Neural Networks
xor
# Making feature vector from Gabor filters for classification using Neural Networks

(Asked by: username_0 on 2013-11-14)

My aim is to classify types of cars (Sedans,SUV,Hatchbacks) and earlier I was using corner features for classification but it didn't work out very well so now I am trying Gabor features.

[code from here](http://www.mathworks.in/matlabcentral/fileexchange/38844-gabor-image-features)

Now the features are extracted and suppose when I give an image as input then for 5 scales and 8 orientations I get 2 [1x40] matrices.

**1. 40 columns of squared Energy.**

**2. 40 colums of mean Amplitude.**

Problem is I want to use these two matrices for classification and I have about 230 images of 3 classes (SUV,sedan,hatchback).

I do not know how to create a [N x 230] matrix which can be taken as vInputs by the neural netowrk in matlab.(where N be the total features of one image).

My question:

1. How to create a one dimensional image vector from the 2 [1x40] matrices for one image.(should I append the mean Amplitude to square energy matrix to get a [1x80] matrix or something else?)
2. Should I be using these gabor features for my purpose of classification in first place? if not then what?

Thanks in advance

**Tags:** machine-learning, image-processing
> **Comments:**
> **username_1**: This question seems more suitable for [stats.se].  
> **username_0**: Ok but I learnt from metastackoverflow that this site can also be useful....anyways I got my answer myself thanks :)  

---

## 0 answers

