Reference point detection for camera-based fingerprint image based on wavelet transformation.
BACKGROUND
Fingerprint recognition systems essentially require core-point detection prior to fingerprint matching. The core-point is used as a reference point to align the fingerprint with a template database. When processing a larger fingerprint database, it is necessary to consider the core-point during feature extraction. Numerous core-point detection methods are available and have been reported in the literature. However, these methods are generally applied to scanner-based images. Hence, this paper attempts to explore the feasibility of applying a core-point detection method to a fingerprint image obtained using a camera phone.


METHODS
The proposed method utilizes a discrete wavelet transform to extract the ridge information from a color image. The performance of proposed method is evaluated in terms of accuracy and consistency. These two indicators are calculated automatically by comparing the method's output with the defined core points.


RESULTS
The proposed method is tested on two data sets, controlled and uncontrolled environment, collected from 13 different subjects. In the controlled environment, the proposed method achieved a detection rate 82.98%. In uncontrolled environment, the proposed method yield a detection rate of 78.21%.


CONCLUSIONS
The proposed method yields promising results in a collected-image database. Moreover, the proposed method outperformed compare to existing method.
Faculty of Commerce and Economics, Sana'a University, Sana'a, Yemen. sayimkhalil@gmail.com.|Center of Excellence Information Assurance, King Saud University, Riyadh, Saudi Arabia. sayimkhalil@gmail.com.
Mohammed S
MS
Khalil
D059925:Anatomic Landmarks / Q000033:anatomy & histology*; D000886:Anthropometry / Q000295:instrumentation / Q000379:methods*; D003878:Dermatoglyphics; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000295:instrumentation*; D059629:Signal-To-Noise Ratio; D000068997:Smartphone; D058067:Wavelet Analysis