Fingerprint feature extraction

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In summary, the conversation is about a person facing problems while executing code for their final year project on fingerprint feature extraction. The first part of the code, which involves pre-processing and image manipulation, works fine. However, the second part, which involves using a function called minutie, fails with an error message stating that the function is undefined. It is suggested that the person may have misspelled the function name as minutie instead of minutiae.
  • #1
babywitch
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Hi, I am currently doing my fyp on fingerprint feature extraction. I am facing a problem inexecuting the code. I'm done with de pre-processing stage on enhancement and so now I’m stuck while using this particular code..

this is the first part:
Matlab:
A = imread('sri2.tif');
[im_row,im_col] = size(A);
binary=im2bw(A);
notbinary=not(binary);
p = bwmorph(notbinary,'clean');
q = bwmorph(p,'fill');
r = bwmorph(q,'skel',Inf);
figure;
imshow(r);

works perfectly fine.

However, the second part fails :

Matlab:
>> fun=@minutie;
r1=nlfilter(r,[3 3],fun);
Matlab:
error : ? Error using ==> feval
Undefined function or method 'minutie' for input arguments of
type 'logical'.

Error in ==> nlfilter at 58
b = mkconstarray(class(feval(fun,aa(1+rows,1+cols),params{:})),
0, size(a));

What is wrong?
 
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  • #2
babywitch said:
fun=@minutie;
There is no such function as minutie. Maybe you are referring to minutiae? That should remove the error.
 

1. What is fingerprint feature extraction?

Fingerprint feature extraction is the process of identifying and isolating the unique characteristics of a fingerprint in order to create a digital representation of it. This digital representation is then used for identification and verification purposes.

2. How does fingerprint feature extraction work?

Fingerprint feature extraction works by using algorithms to analyze the ridges, valleys, and other unique details of a fingerprint. These features are then extracted and converted into a digital template that can be compared to other fingerprints in a database.

3. What are the common methods used for fingerprint feature extraction?

The common methods used for fingerprint feature extraction include minutiae-based methods, ridge-based methods, and hybrid methods. Minutiae-based methods focus on identifying and extracting the specific points where ridges end or bifurcate. Ridge-based methods analyze the overall pattern of ridges and valleys. Hybrid methods combine both minutiae and ridge-based approaches.

4. What are the benefits of fingerprint feature extraction?

Fingerprint feature extraction has several benefits, including high accuracy and reliability for identification and verification, ease of use, and low cost compared to other biometric methods. It also provides a non-intrusive and non-invasive way of identifying individuals.

5. What are the potential applications of fingerprint feature extraction?

Fingerprint feature extraction has a wide range of potential applications, including law enforcement and criminal investigations, border control and immigration, access control for buildings and devices, and time and attendance tracking. It can also be used for personal identification in banking and financial transactions, and for medical record management.

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