Shweta Warade - Academia.edu (original) (raw)

Papers by Shweta Warade

International Journal of Innovative Research in Computer and Communication Engineering, 2015

Fingerprint biometrics provides identity verification with a strong degree of confidence over pas... more Fingerprint biometrics provides identity verification with a strong degree of confidence over past few decades. Present work focuses on special branch of fingerprint recognition namely, touch-less fingerprint recognition which has fundamental advantage in terms of better hygiene, safety and latent fingerprints over traditional touch-based systems. Such systems find applications in numerous fields such as secure access to laptops and computer systems, cellular phones, banking, ATMs etc. Although lot of work have been done on touch-less fingerprint recognition systems, still people are looking for more accuracy. The proposed touch-less fingerprint recognition system opt digital camera as the device to acquire the fingerprint image and it consists of three main steps: Pre-processing, Feature extraction and Verification. Current work presents a comparative performance evaluation of two widely used classifiers: Support Vector Machine (SVM) and Gaussian Mixture Model (GMM). Experimental r...

Fingerprint recognition has aided variety of biometric security applications over past few decade... more Fingerprint recognition has aided variety of biometric security applications over past few decades. Each person possesses unique fingerprint characteristic in terms of minutia, pore, ridges and patterns. Based on data acquisition methods fingerprint recognition can be touch based or touch less, with later having advantage in terms of better hygiene, safety and stray fingerprints. In Touch-less fingerprint recognition, fingerprints are acquired using a high resolution digital camera or any other optical acquisition system. Such systems find applications in numerous fields such as secure access to laptops, computer systems, cellular phones, banking, ATMs etc. Deceiving the simple appearance various taxing, such as non-uniform light, movement blurriness, defocus and low contrast between ridges and valley etc. To overcome such problems, it is important to focus more on the pre-processing steps. Touch-less fingerprint detection can be classified as two-dimensional and three-dimensional m...

Fingerprint biometrics provides identity verification with a strong degree of confidence over pas... more Fingerprint biometrics provides identity verification with a strong degree of confidence over past few
decades. Present work focuses on special branch of fingerprint recognition namely, touch-less fingerprint recognition
which has fundamental advantage in terms of better hygiene, safety and latent fingerprints over traditional touch-based
systems. Such systems find applications in numerous fields such as secure access to laptops and computer systems,
cellular phones, banking, ATMs etc. Although lot of work have been done on touch-less fingerprint recognition
systems, still people are looking for more accuracy. The proposed touch-less fingerprint recognition system opt digital
camera as the device to acquire the fingerprint image and it consists of three main steps: Pre-processing, Feature
extraction and Verification. Current work presents a comparative performance evaluation of two widely used
classifiers: Support Vector Machine (SVM) and Gaussian Mixture Model (GMM). Experimental results illustrates that
GMM shows slightly better accuracy than SVM.

Fingerprint recognition has aided variety of biometric security applications over past few decade... more Fingerprint recognition has aided variety of biometric security applications over past few decades. Each person possesses
unique fingerprint characteristic in terms of minutia, pore, ridges and patterns. Based on data acquisition methods fingerprint
recognition can be touch based or touch less, with later having advantage in terms of better hygiene, safety and stray fingerprints. In
Touch-less fingerprint recognition, fingerprints are acquired using a high resolution digital camera or any other optical acquisition
system. Such systems find applications in numerous fields such as secure access to laptops, computer systems, cellular phones, banking,
ATMs etc. Deceiving the simple appearance various taxing, such as non-uniform light, movement blurriness, defocus and low contrast
between ridges and valley etc. To overcome such problems, it is important to focus more on the pre-processing steps. Touch-less
fingerprint detection can be classified as two-dimensional and three-dimensional methods depending upon number of cameras used for
acquisition of finger-print image. Literature presents different techniques for acquisition and analysis of finger-print images. In this
paper, an effort is being made to review some of these techniques and give a brief comparison for the same in terms of accuracy, merits,
demerits and their respective solution.

International Journal of Innovative Research in Computer and Communication Engineering, 2015

Fingerprint biometrics provides identity verification with a strong degree of confidence over pas... more Fingerprint biometrics provides identity verification with a strong degree of confidence over past few decades. Present work focuses on special branch of fingerprint recognition namely, touch-less fingerprint recognition which has fundamental advantage in terms of better hygiene, safety and latent fingerprints over traditional touch-based systems. Such systems find applications in numerous fields such as secure access to laptops and computer systems, cellular phones, banking, ATMs etc. Although lot of work have been done on touch-less fingerprint recognition systems, still people are looking for more accuracy. The proposed touch-less fingerprint recognition system opt digital camera as the device to acquire the fingerprint image and it consists of three main steps: Pre-processing, Feature extraction and Verification. Current work presents a comparative performance evaluation of two widely used classifiers: Support Vector Machine (SVM) and Gaussian Mixture Model (GMM). Experimental r...

Fingerprint recognition has aided variety of biometric security applications over past few decade... more Fingerprint recognition has aided variety of biometric security applications over past few decades. Each person possesses unique fingerprint characteristic in terms of minutia, pore, ridges and patterns. Based on data acquisition methods fingerprint recognition can be touch based or touch less, with later having advantage in terms of better hygiene, safety and stray fingerprints. In Touch-less fingerprint recognition, fingerprints are acquired using a high resolution digital camera or any other optical acquisition system. Such systems find applications in numerous fields such as secure access to laptops, computer systems, cellular phones, banking, ATMs etc. Deceiving the simple appearance various taxing, such as non-uniform light, movement blurriness, defocus and low contrast between ridges and valley etc. To overcome such problems, it is important to focus more on the pre-processing steps. Touch-less fingerprint detection can be classified as two-dimensional and three-dimensional m...

Fingerprint biometrics provides identity verification with a strong degree of confidence over pas... more Fingerprint biometrics provides identity verification with a strong degree of confidence over past few
decades. Present work focuses on special branch of fingerprint recognition namely, touch-less fingerprint recognition
which has fundamental advantage in terms of better hygiene, safety and latent fingerprints over traditional touch-based
systems. Such systems find applications in numerous fields such as secure access to laptops and computer systems,
cellular phones, banking, ATMs etc. Although lot of work have been done on touch-less fingerprint recognition
systems, still people are looking for more accuracy. The proposed touch-less fingerprint recognition system opt digital
camera as the device to acquire the fingerprint image and it consists of three main steps: Pre-processing, Feature
extraction and Verification. Current work presents a comparative performance evaluation of two widely used
classifiers: Support Vector Machine (SVM) and Gaussian Mixture Model (GMM). Experimental results illustrates that
GMM shows slightly better accuracy than SVM.

Fingerprint recognition has aided variety of biometric security applications over past few decade... more Fingerprint recognition has aided variety of biometric security applications over past few decades. Each person possesses
unique fingerprint characteristic in terms of minutia, pore, ridges and patterns. Based on data acquisition methods fingerprint
recognition can be touch based or touch less, with later having advantage in terms of better hygiene, safety and stray fingerprints. In
Touch-less fingerprint recognition, fingerprints are acquired using a high resolution digital camera or any other optical acquisition
system. Such systems find applications in numerous fields such as secure access to laptops, computer systems, cellular phones, banking,
ATMs etc. Deceiving the simple appearance various taxing, such as non-uniform light, movement blurriness, defocus and low contrast
between ridges and valley etc. To overcome such problems, it is important to focus more on the pre-processing steps. Touch-less
fingerprint detection can be classified as two-dimensional and three-dimensional methods depending upon number of cameras used for
acquisition of finger-print image. Literature presents different techniques for acquisition and analysis of finger-print images. In this
paper, an effort is being made to review some of these techniques and give a brief comparison for the same in terms of accuracy, merits,
demerits and their respective solution.