Abstract:
The quality of fingerprint image greatly affects the performance of minutiae extraction and the process of matching in fingerprint identification system. In order to improve the performance of the fingerprint identification system, a fuzzy techniques used for bothfingerprint image quality analysis and enhancement.
First, the quality analysis performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). Afuzzy logic technique that uses Mamdani fuzzy rule model was designed. The fuzzy inference system was able toanalyze and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and fuzzy inference rules.
The experimental result obtained using the fuzzy technique were successful, and was able to determine the fingerprint image quality (Oily, Neutral, or Dry) according to their input features.
Secondly, fuzzy morphology was applied to enhance dry and oily fingerprint images.Fuzzy morphology method improves the quality of a fingerprint image, thus, improving the performance of the fingerprint identification system significantly.
All the experimental work which was done for both quality analysis and image enhancementwas done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology SepuluhNopember Surabaya, Indonesia.
The performance evaluation was done by using Feature Similarity index (FSIM). Where the FSIMis an image quality assessment (IQA) metric, whichuses computational models to measure the image quality consistently with subjective evaluations.
