How to study the effectiveness of feature extraction ?
1 view (last 30 days)
Show older comments
I am working on the extraction of fine detailed features in fingerprint mainly pores(white blobs). Now I need to validate the proposed extraction process,most of the research work checks it through state of art matching algorithms.I cannot implement those matching algorithms in the limited time available.How else can I justify my extraction process?
0 Comments
Answers (2)
Jeff E
on 1 May 2015
Manually identify the pores in a (small) set of images, and compare the two results. Ideally by looking at the overlapping and non-overlapping events and computing the confusion matrix.
3 Comments
Jeff E
on 1 May 2015
When you manually define your pores, use roipoly to create a binary mask. You can then compare the manually annotated mask to the one you need to validate, with the manual mask serving as the ground truth.
true_positive = bwarea(manual_mask & automated_mask) ;
true_negative = bwarea(~manual_mask & ~automated_mask) ;
false_positive = bwarea(~manual_mask & auotmated_mask) ;
false_negative = bwarea(manual_mask & ~automated_mask) ;
Image Analyst
on 1 May 2015
The usual method is to construct an ROC curve.
"ROC analysis since then has been used in medicine, radiology, biometrics, and other areas for many decades and is increasingly used in machine learning and data mining research........"
This is a good opportunity for you to learn about it.
See Also
Categories
Find more on Image Segmentation and Analysis in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!