�ݺ�ߣshows by User: AngeloGenovese

�ݺ�ߣshows by User: AngeloGenovese / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: AngeloGenovese / Fri, 08 Jan 2016 13:11:02 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: AngeloGenovese Touchless and less-constrained 3D fingerprint recognition /slideshow/touchless-and-lessconstrained-3d-fingerprint-recognition/56824645 genovese-touchless3dfingerprint-160108131102
Biometrics Fingerprint biometrics Touchless fingerprint biometrics Proposed touchless 3D fingerprint recognition Computation of synthetic 3D fingerprint samples Touchless 3D reconstruction of ancient fingerprints Conclusions]]>
Biometrics Fingerprint biometrics Touchless fingerprint biometrics Proposed touchless 3D fingerprint recognition Computation of synthetic 3D fingerprint samples Touchless 3D reconstruction of ancient fingerprints Conclusions]]> Fri, 08 Jan 2016 13:11:02 GMT /slideshow/touchless-and-lessconstrained-3d-fingerprint-recognition/56824645 AngeloGenovese@slideshare.net(AngeloGenovese) Touchless and less-constrained 3D fingerprint recognition AngeloGenovese Biometrics Fingerprint biometrics Touchless fingerprint biometrics Proposed touchless 3D fingerprint recognition Computation of synthetic 3D fingerprint samples Touchless 3D reconstruction of ancient fingerprints Conclusions <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/genovese-touchless3dfingerprint-160108131102-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Biometrics Fingerprint biometrics Touchless fingerprint biometrics Proposed touchless 3D fingerprint recognition Computation of synthetic 3D fingerprint samples Touchless 3D reconstruction of ancient fingerprints Conclusions

Touchless and less-constrained 3D fingerprint recognition from Angelo Genovese

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0 Elaborazione tridimensionale di impronte digitali acquisite senza contatto - Presentazione M.Sc. /AngeloGenovese/presentation-41503779 presentation-141113054117-conversion-gate01
The purpose of this work has been the computation of three-dimensional models of the finger and the fingerprint by using techniques based on multiple views of the finger, acquired without contact to the sensor. Three-dimensional models have then been processed in order to produce images comparable with those taken by traditional contact-based sensors. The contents of this work can be divided in the following steps. After calibrating the cameras, the obtained images were processed to extract some features from them (e.g., the finger boundary, the region of interest, the frequency and orientation of the ridges, and the location of some particular points). The images were processed by using a sequence of algorithms in order to make them similar to traditional contact-based fingerprint acquisitions. From the resulting images typical fingerprint features, such as minutiae position and ridge pattern, were then extracted. The information obtained in this process was used to build three-dimensional models. Two approaches are described in this thesis. The former is based on minutiae triangulation and consists of a discrete reconstruction of the fingerprint features. The latter uses a few loci (such as the point of maximum ridge curvature) extracted from multiple images and approximates a three-dimensional volume eventually completed with the superimposition of the original images. The resulting three-dimensional models are then transformed into planar images, so that state-of-the-art algorithms can extract the fingerprint features and compare them with the features extracted from traditional images.]]>
The purpose of this work has been the computation of three-dimensional models of the finger and the fingerprint by using techniques based on multiple views of the finger, acquired without contact to the sensor. Three-dimensional models have then been processed in order to produce images comparable with those taken by traditional contact-based sensors. The contents of this work can be divided in the following steps. After calibrating the cameras, the obtained images were processed to extract some features from them (e.g., the finger boundary, the region of interest, the frequency and orientation of the ridges, and the location of some particular points). The images were processed by using a sequence of algorithms in order to make them similar to traditional contact-based fingerprint acquisitions. From the resulting images typical fingerprint features, such as minutiae position and ridge pattern, were then extracted. The information obtained in this process was used to build three-dimensional models. Two approaches are described in this thesis. The former is based on minutiae triangulation and consists of a discrete reconstruction of the fingerprint features. The latter uses a few loci (such as the point of maximum ridge curvature) extracted from multiple images and approximates a three-dimensional volume eventually completed with the superimposition of the original images. The resulting three-dimensional models are then transformed into planar images, so that state-of-the-art algorithms can extract the fingerprint features and compare them with the features extracted from traditional images.]]> Thu, 13 Nov 2014 05:41:17 GMT /AngeloGenovese/presentation-41503779 AngeloGenovese@slideshare.net(AngeloGenovese) Elaborazione tridimensionale di impronte digitali acquisite senza contatto - Presentazione M.Sc. AngeloGenovese The purpose of this work has been the computation of three-dimensional models of the finger and the fingerprint by using techniques based on multiple views of the finger, acquired without contact to the sensor. Three-dimensional models have then been processed in order to produce images comparable with those taken by traditional contact-based sensors. The contents of this work can be divided in the following steps. After calibrating the cameras, the obtained images were processed to extract some features from them (e.g., the finger boundary, the region of interest, the frequency and orientation of the ridges, and the location of some particular points). The images were processed by using a sequence of algorithms in order to make them similar to traditional contact-based fingerprint acquisitions. From the resulting images typical fingerprint features, such as minutiae position and ridge pattern, were then extracted. The information obtained in this process was used to build three-dimensional models. Two approaches are described in this thesis. The former is based on minutiae triangulation and consists of a discrete reconstruction of the fingerprint features. The latter uses a few loci (such as the point of maximum ridge curvature) extracted from multiple images and approximates a three-dimensional volume eventually completed with the superimposition of the original images. The resulting three-dimensional models are then transformed into planar images, so that state-of-the-art algorithms can extract the fingerprint features and compare them with the features extracted from traditional images. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/presentation-141113054117-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> The purpose of this work has been the computation of three-dimensional models of the finger and the fingerprint by using techniques based on multiple views of the finger, acquired without contact to the sensor. Three-dimensional models have then been processed in order to produce images comparable with those taken by traditional contact-based sensors. The contents of this work can be divided in the following steps. After calibrating the cameras, the obtained images were processed to extract some features from them (e.g., the finger boundary, the region of interest, the frequency and orientation of the ridges, and the location of some particular points). The images were processed by using a sequence of algorithms in order to make them similar to traditional contact-based fingerprint acquisitions. From the resulting images typical fingerprint features, such as minutiae position and ridge pattern, were then extracted. The information obtained in this process was used to build three-dimensional models. Two approaches are described in this thesis. The former is based on minutiae triangulation and consists of a discrete reconstruction of the fingerprint features. The latter uses a few loci (such as the point of maximum ridge curvature) extracted from multiple images and approximates a three-dimensional volume eventually completed with the superimposition of the original images. The resulting three-dimensional models are then transformed into planar images, so that state-of-the-art algorithms can extract the fingerprint features and compare them with the features extracted from traditional images.

Elaborazione tridimensionale di impronte digitali acquisite senza contatto - Presentazione M.Sc. from Angelo Genovese

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0 Contactless and less-constrained palmprint recognition - Ph.D. presentation /slideshow/contactless-and-lessconstrained-palmprint-recognition-phd-presentation/41503288 phdpresentationgenovesefinalv4-141113052758-conversion-gate02
This thesis has the objective of researching innovative methods for the contactless and less-constrained recognition of the palmprint. In particular, the researched methods allow to recognize the individuals without the contact of the hand with any surface, and a metric three-dimensional representation is used to eliminate the need for the user to place his hand in a specific position. The originality of the researched techniques allow to perform an accurate biometric recognition, with a focus on the usability, computational speed, and social acceptance of the system. Moreover, the cost of the final device is also taken into consideration. The novelty of the described method, with respect to similar methods in the literature based on contactless three-dimensional acquisitions, resides in the use of an innovative setup, which has a lower cost and captures the images faster.]]>
This thesis has the objective of researching innovative methods for the contactless and less-constrained recognition of the palmprint. In particular, the researched methods allow to recognize the individuals without the contact of the hand with any surface, and a metric three-dimensional representation is used to eliminate the need for the user to place his hand in a specific position. The originality of the researched techniques allow to perform an accurate biometric recognition, with a focus on the usability, computational speed, and social acceptance of the system. Moreover, the cost of the final device is also taken into consideration. The novelty of the described method, with respect to similar methods in the literature based on contactless three-dimensional acquisitions, resides in the use of an innovative setup, which has a lower cost and captures the images faster.]]> Thu, 13 Nov 2014 05:27:57 GMT /slideshow/contactless-and-lessconstrained-palmprint-recognition-phd-presentation/41503288 AngeloGenovese@slideshare.net(AngeloGenovese) Contactless and less-constrained palmprint recognition - Ph.D. presentation AngeloGenovese This thesis has the objective of researching innovative methods for the contactless and less-constrained recognition of the palmprint. In particular, the researched methods allow to recognize the individuals without the contact of the hand with any surface, and a metric three-dimensional representation is used to eliminate the need for the user to place his hand in a specific position. The originality of the researched techniques allow to perform an accurate biometric recognition, with a focus on the usability, computational speed, and social acceptance of the system. Moreover, the cost of the final device is also taken into consideration. The novelty of the described method, with respect to similar methods in the literature based on contactless three-dimensional acquisitions, resides in the use of an innovative setup, which has a lower cost and captures the images faster. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/phdpresentationgenovesefinalv4-141113052758-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> This thesis has the objective of researching innovative methods for the contactless and less-constrained recognition of the palmprint. In particular, the researched methods allow to recognize the individuals without the contact of the hand with any surface, and a metric three-dimensional representation is used to eliminate the need for the user to place his hand in a specific position. The originality of the researched techniques allow to perform an accurate biometric recognition, with a focus on the usability, computational speed, and social acceptance of the system. Moreover, the cost of the final device is also taken into consideration. The novelty of the described method, with respect to similar methods in the literature based on contactless three-dimensional acquisitions, resides in the use of an innovative setup, which has a lower cost and captures the images faster.

Contactless and less-constrained palmprint recognition - Ph.D. presentation from Angelo Genovese

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0 https://cdn.slidesharecdn.com/profile-photo-AngeloGenovese-48x48.jpg?cb=1666942613 Angelo Genovese was born in Benevento, Italy, on February 19th, 1985. He received the B.Sc., M.Sc., and Ph.D. degrees in Computer Science in 2007, 2010, and 2014 respectively, from Università degli Studi di Milano, Italy. From September 2010 to December 2010 he held a scholarship from the Università degli Studi di Milano, Italy. Since January 2014 he is a Research associate at Università degli Studi di Milano, Italy, Department of Computer Science. Since 2010 he is a member of the Biometric Systems Laboratory and the Industrial and Environmental Informatics Laboratory, at the Department of Computer Science, Università degli Studi di Milano, Italy. http://homes.di.unimi.it/genovese https://cdn.slidesharecdn.com/ss_thumbnails/genovese-touchless3dfingerprint-160108131102-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/touchless-and-lessconstrained-3d-fingerprint-recognition/56824645 Touchless and less-con... https://cdn.slidesharecdn.com/ss_thumbnails/presentation-141113054117-conversion-gate01-thumbnail.jpg?width=320&height=320&fit=bounds AngeloGenovese/presentation-41503779 Elaborazione tridimens... https://cdn.slidesharecdn.com/ss_thumbnails/phdpresentationgenovesefinalv4-141113052758-conversion-gate02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/contactless-and-lessconstrained-palmprint-recognition-phd-presentation/41503288 Contactless and less-c...