# find the most similar vector from 10 vectors

2 vues (au cours des 30 derniers jours)
talayeh ghodsi le 30 Juin 2019
Modifié(e) : Stephen23 le 30 Juin 2019
hello every one.
I have one echo image and 10 ct images. i have extract Local binary pattern of them, and i have calculated the squared error between lbp of echo and lbp of each of the 10 ct images. now could anyone answer me how can i find the most similar ct image to echo image from 10 squared errors?
lbpct124 = extractLBPFeatures(ct124,'Upright',false);
lbpct125 = extractLBPFeatures(ct125,'Upright',false);
lbpct126 = extractLBPFeatures(ct126,'Upright',false);
lbpct127 = extractLBPFeatures(ct127,'Upright',false);
lbpct128 = extractLBPFeatures(ct128,'Upright',false);
lbpct129 = extractLBPFeatures(ct129,'Upright',false);
lbpct130 = extractLBPFeatures(ct130,'Upright',false);
lbpct131 = extractLBPFeatures(ct131,'Upright',false);
lbpct132 = extractLBPFeatures(ct132,'Upright',false);
lbpct133 = extractLBPFeatures(ct133,'Upright',false);
lbpct134 = extractLBPFeatures(ct134,'Upright',false);
lbpct135 = extractLBPFeatures(ct135,'Upright',false);
lbpct136 = extractLBPFeatures(ct136,'Upright',false);
lbpct137 = extractLBPFeatures(ct137,'Upright',false);
lbpct138 = extractLBPFeatures(ct138,'Upright',false);
lbpecho = extractLBPFeatures(echo,'Upright',false);
echoVsct124 = (lbpecho - lbpct124).^2;
echoVsct125 = (lbpecho - lbpct125).^2;
echoVsct126 = (lbpecho - lbpct126).^2;
echoVsct127 = (lbpecho - lbpct127).^2;
echoVsct128 = (lbpecho - lbpct128).^2;
echoVsct129 = (lbpecho - lbpct129).^2;
echoVsct130 = (lbpecho - lbpct130).^2;
echoVsct131 = (lbpecho - lbpct131).^2;
echoVsct132 = (lbpecho - lbpct132).^2;
echoVsct133 = (lbpecho - lbpct133).^2;
echoVsct134 = (lbpecho - lbpct134).^2;
echoVsct135 = (lbpecho - lbpct135).^2;
echoVsct136 = (lbpecho - lbpct136).^2;
echoVsct137 = (lbpecho - lbpct137).^2;
echoVsct138 = (lbpecho - lbpct138).^2;
figure
bar([echoVsct124; echoVsct125; echoVsct126; echoVsct127; echoVsct128; echoVsct129; echoVsct130; echoVsct131; echoVsct132; echoVsct133; echoVsct134; echoVsct135; echoVsct136; echoVsct137; echoVsct138]','grouped')
title('Squared Error of LBP Histograms')
xlabel('LBP Histogram Bins')
legend('echo vs ct124','echo vs ct125','echo vs ct126','echo vs ct127','echo vs ct128','echo vs ct129','echo vs ct130','echo vs ct131','echo vs ct132','echo vs ct133','echo vs ct134','echo vs ct135','echo vs ct136','echo vs ct137','echo vs ct138')
##### 2 commentairesAfficher AucuneMasquer Aucune
Stephen23 le 30 Juin 2019
Modifié(e) : Stephen23 le 30 Juin 2019
Note that copy-and-pasting code is a sign that you are doing something wrong.
Note that using numbered variables is a sign that you are doing something wrong.
You would be much better of using indexing, exactly as shown in the MATLAB documentation:
talayeh ghodsi le 30 Juin 2019
is it possible for you to tell me how? could you please rewrite my code in simple way? sorry i am a beginner in matlab

Connectez-vous pour commenter.

### Réponses (1)

Image Analyst le 30 Juin 2019
Have you tried similarity metrics such as ssim(), immse(), and psnr()?
##### 1 commentaireAfficher -1 commentaires plus anciensMasquer -1 commentaires plus anciens
talayeh ghodsi le 30 Juin 2019
sorry but the images are multimodal, i have extract features of images (LBP) and now i want to find the best match features
i have 1 vector of feature from calss A,which is 1*10 against 10 vector of features from calss B each is 1*10
i want to find the best feature vector from class B to be the most similar to feature vector of class A

Connectez-vous pour commenter.

### Catégories

En savoir plus sur LBP - Local Binary Patterns dans Help Center et File Exchange

### Community Treasure Hunt

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

Start Hunting!

Translated by