How to do feature extraction from an image?

1 view (last 30 days)
sara
sara on 2 Aug 2020
Commented: sara on 31 Aug 2020
Hi I want to do feature extraction from an image. I read a paper and did this steps: I did image segmentation. Then I want to do feature extraction. In this paper:
Segmented lungs were divided into 3*3 windows in which all nine pixels were located in the lung mask. Window size selection is a compromise between higher resolution (in the classification process) and faster algorithm. Smaller windows (i.e. 1*1 or 2*2) have the problem of more time complexity for training and increaseing the number of FP. Larger windows (i.e. 5* 5 or larger) cause lower resolution of reconstructed image after classification and miss some tiny nodules. Thus, for better resolution and faster algorithm, simultaneously, we used a 3*3 window. In the training process, these windows were labeled as nodule (þ1) and non-nodule (1).
My question is this: Is there any standard criteria to lable the 3*3 window as a noudle? ( I mean if how many of these pixcles are 1, we should lable the window as a noudle?)</pre>
  12 Comments
Image Analyst
Image Analyst on 4 Aug 2020
I don't think they segmented the image. I think they did that on the original gray scale image. I don't think it would make any sense to do a covariance of 9 pixels if the 9 pixels were segmented, which means they are already binary/logical.
sara
sara on 31 Aug 2020
thanks dear Image Analyst. I think I made a mistake. I read the paper again. I knew they segment region of interested from background and then they do this operation on gray scale image.

Sign in to comment.

Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!