Abstract: An optical module includes a housing with a lighting mechanism, an aperture formed therein, and a window that frames a transparent surface adapted to contact a skin surface of a person, for example, a fingertip. The lighting mechanism provides light to illuminate the skin surface placed upon the transparent surface. A prism has a first side facing the lighting mechanism, a second side at the window, and a third side through which a dactylographic image exits the prism. One or more light reflecting surfaces are disposed within the housing to reflect the dactylographic image towards the housing aperture. The optical module is coupled to a mobile device having a camera, with the aperture of the housing aligning with a lens of the camera. The camera acquires the dactylographic image, and the mobile device adjusts this dactylographic image to produce a dactylographic image suitable for biometric matching.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: An optical module includes a housing with a lighting mechanism, an aperture formed therein, and a window that frames a transparent surface adapted to contact a skin surface of a person, for example, a fingertip. The lighting mechanism provides light to illuminate the skin surface placed upon the transparent surface. A prism has a first side facing the lighting mechanism, a second side at the window, and a third side through which a dactylographic image exits the prism. One or more light reflecting surfaces are disposed within the housing to reflect the dactylographic image towards the housing aperture. The optical module is coupled to a mobile device having a camera, with the aperture of the housing aligning with a lens of the camera. The camera acquires the dactylographic image, and the mobile device adjusts this dactylographic image to produce a dactylographic image suitable for biometric matching.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: An optical module includes a housing with a lighting mechanism, an aperture formed therein, and a window that frames a transparent surface adapted to contact a skin surface of a person, for example, a fingertip. The lighting mechanism provides light to illuminate the skin surface placed upon the transparent surface. A prism has a first side facing the lighting mechanism, a second side at the window, and a third side through which a dactylographic image exits the prism. One or more light reflecting surfaces are disposed within the housing to reflect the dactylographic image towards the housing aperture. The optical module is coupled to a mobile device having a camera, with the aperture of the housing aligning with a lens of the camera. The camera acquires the dactylographic image, and the mobile device adjusts this dactylographic image to produce a dactylographic image suitable for biometric matching.

Abstract: An optical module includes a housing with a lighting mechanism, an aperture formed therein, and a window that frames a transparent surface adapted to contact a skin surface of a person, for example, a fingertip. The lighting mechanism provides light to illuminate the skin surface placed upon the transparent surface. A prism has a first side facing the lighting mechanism, a second side at the window, and a third side through which a dactylographic image exits the prism. One or more light reflecting surfaces are disposed within the housing to reflect the dactylographic image towards the housing aperture. The optical module is coupled to a mobile device having a camera, with the aperture of the housing aligning with a lens of the camera. The camera acquires the dactylographic image, and the mobile device adjusts this dactylographic image to produce a dactylographic image suitable for biometric matching.

Abstract: An optical module includes a housing with a lighting mechanism, an aperture formed therein, and a window that frames a transparent surface adapted to contact a skin surface of a person, for example, a fingertip. The lighting mechanism provides light to illuminate the skin surface placed upon the transparent surface. A prism has a first side facing the lighting mechanism, a second side at the window, and a third side through which a dactylographic image exits the prism. One or more light reflecting surfaces are disposed within the housing to reflect the dactylographic image towards the housing aperture. The optical module is coupled to a mobile device having a camera, with the aperture of the housing aligning with a lens of the camera. The camera acquires the dactylographic image, and the mobile device adjusts this dactylographic image to produce a dactylographic image suitable for biometric matching.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: An optical module includes a housing with a lighting mechanism, an aperture formed therein, and a window that frames a transparent surface adapted to contact a skin surface of a person, for example, a fingertip. The lighting mechanism provides light to illuminate the skin surface placed upon the transparent surface. A prism has a first side facing the lighting mechanism, a second side at the window, and a third side through which a dactylographic image exits the prism. One or more light reflecting surfaces are disposed within the housing to reflect the dactylographic image towards the housing aperture. The optical module is coupled to a mobile device having a camera, with the aperture of the housing aligning with a lens of the camera. The camera acquires the dactylographic image, and the mobile device adjusts this dactylographic image to produce a dactylographic image suitable for biometric matching.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: Systems and methods for enhancing confidence in a biometric search result include submitting one or more biometric samples to a biometric search engine. In response to the one or more submitted biometric samples, a plurality of candidates identified as potentially associated with the one or more submitted biometric samples is received from the biometric search engine. Each identified candidate has associated biographic information. The biographic information associated with each identified candidate is submitted to a relationship detection engine. In response to the submitted biographic information, an identified relationship between at least one of the identified candidates and one or more other individuals is received from the relationship detection engine.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.