Abstract
The advancement of science and technology has made the reliable individual recognition and identification systems to become very popular. From the various biometric characteristics, fingerprint is one of the popular method because of its easiness and not much effort is required to acquire fingerprint. First step for an Automated Fingerprint Identification System (AFIS) is the segmentation of fingerprint from the acquired image. During fingerprint segmentation process the input image is decomposed into foreground and background areas. The foreground area contains information that are needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false features. So in an AFIS, fingerprint image segmentation plays an important role in carefully separating ridge like part (foreground) from noisy background. Gradient based method is commonly used for segmentation process. Since gradient estimation is erroneous in noisy images, the study proposes a combination of gradient mask and morphological operations to segment fingerprint foreground effectively. The results obtained prove that the new method is suited for fingerprint segmentation.
Highlights
Along with the technological advancement, the reliable individual recognition and identification system became very important
Since gradient estimation is erroneous in noisy images, the study proposes a combination of gradient mask and morphological operations to segment fingerprint foreground effectively
The proposed fingerprint segmentation method has been tested with a standard Verifinger Sample DB dataset taken form Neurotechnologija web site [12]
Summary
Along with the technological advancement, the reliable individual recognition and identification system became very important. Fingertip contains a pattern of ridges and valleys that are parallel to each other Fingerprint image segmentation plays an inevitable role in the extraction of valid features. In [1], a segmentation algorithm based on local pixel features like mean, variance and coherence is proposed. The linear combination of these features are taken for segmentation The limitation of this technique is its low speed. They are affected by noises as gradients are calculated based on pixel This may lead a true ridge like region to identify as a noisy background area. Morphological operations combined with the gradient mask is used in this paper to resolve this problem and to get the final segmented fingerprint image.
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