Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection
نویسندگان
چکیده
منابع مشابه
Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection
We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by compar...
متن کاملLocal contrast phase descriptor for fingerprint liveness detection
We propose a new local descriptor for fingerprint liveness detection. The input image is analyzed both in the spatial and in the frequency domain, in order to extract information on the local amplitude contrast, and on the local behavior of the image, synthesized by considering the phase of some selected transform coefficients. These two pieces of information are used to generate a bi-dimension...
متن کاملLiveness Detection for Fingerprint Biometrics
Biometrics refers to automated recognition of individuals based on their biological and behavioral characteristics. Biometric systems are widely used for security. They are used in forensic and commercial applications. Among all biometric techniques, fingerprint recognition is the most widely used for personal identification systems due to its permanence and uniqueness. But biometric systems ar...
متن کاملWavelet Based Fingerprint Liveness Detection
We propose a simple and effective approach for fingerprint liveness detection based on the wavelet analysis of the finger tip surface texture. Experimental results show that our method can successfully differentiate live finger tips from fake finger tips made of most commonly used material in fingerprint spoofing.
متن کاملOn Multiview Analysis for Fingerprint Liveness Detection
Fingerprint recognition systems, as any other biometric system, can be subject to attacks, which are usually carried out using artificial fingerprints. Several approaches to discriminate between live and fake fingerprint images have been presented to address this issue. These methods usually rely on the analysis of individual features extracted from the fingerprint images. Such features represe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLOS ONE
سال: 2016
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0148552