2014
DOI: 10.1016/j.ins.2014.02.031
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Hand shape identification on multirange images

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Cited by 18 publications
(4 citation statements)
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“…Several hardware and software-specific fundamental techniques are deployed for PAD in the biometric contexts. In the hardware-based method, an expensive sensor is employed for image acquisition from which the constraints about liveness such as the thermal facial map, blood pressure, perspiration, hand-vein temperature, and other salient features are computed [20], [24], [31], [51], [17]. Technological advancements of the sensor devices offer to acquire the thermal [20], [24], [51], [17], [4] and hyperspectral [25] images, which direct to devise high-security measures such as liveness detection to discard the fake hand biometric samples.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Several hardware and software-specific fundamental techniques are deployed for PAD in the biometric contexts. In the hardware-based method, an expensive sensor is employed for image acquisition from which the constraints about liveness such as the thermal facial map, blood pressure, perspiration, hand-vein temperature, and other salient features are computed [20], [24], [31], [51], [17]. Technological advancements of the sensor devices offer to acquire the thermal [20], [24], [51], [17], [4] and hyperspectral [25] images, which direct to devise high-security measures such as liveness detection to discard the fake hand biometric samples.…”
Section: Introductionmentioning
confidence: 99%
“…In the hardware-based method, an expensive sensor is employed for image acquisition from which the constraints about liveness such as the thermal facial map, blood pressure, perspiration, hand-vein temperature, and other salient features are computed [20], [24], [31], [51], [17]. Technological advancements of the sensor devices offer to acquire the thermal [20], [24], [51], [17], [4] and hyperspectral [25] images, which direct to devise high-security measures such as liveness detection to discard the fake hand biometric samples. On the contrary, the software-based method discriminates between the real and counterfeit images using a computable characteristic, such as visual quality assessment [57], [45], [49], [52], [29], [48], [30], [37].…”
Section: Introductionmentioning
confidence: 99%
“…Several hardware and software-specific fundamental techniques are deployed for PAD in the biometric contexts. In the hardware-based method, an expensive sensor is employed for image acquisition from which the constraints about liveness such as the thermal facial map, blood pressure, perspiration, hand-vein temperature, and other salient features are computed Czajka and Bulwan [2013], Faundez-Zanuy et al [2014], Harvey et al [2018], Travieso et al [2014], Chen et al [2016]. Technological advancements of the sensor devices offer to acquire the thermal Czajka and Bulwan [2013], Faundez-Zanuy et al [2014], Travieso et al [2014], Chen et al [2016], Bartuzi and Trokielewicz [2018] and hyperspectral Ferrer et al [2014] images, which direct to devise high-security measures such as liveness detection to discard the fake hand biometric samples.…”
Section: Introductionmentioning
confidence: 99%
“…In the hardware-based method, an expensive sensor is employed for image acquisition from which the constraints about liveness such as the thermal facial map, blood pressure, perspiration, hand-vein temperature, and other salient features are computed Czajka and Bulwan [2013], Faundez-Zanuy et al [2014], Harvey et al [2018], Travieso et al [2014], Chen et al [2016]. Technological advancements of the sensor devices offer to acquire the thermal Czajka and Bulwan [2013], Faundez-Zanuy et al [2014], Travieso et al [2014], Chen et al [2016], Bartuzi and Trokielewicz [2018] and hyperspectral Ferrer et al [2014] images, which direct to devise high-security measures such as liveness detection to discard the fake hand biometric samples. On the contrary, the software-based method discriminates between the real and counterfeit images using a computable characteristic, such as visual quality assessment Zhang et al [2013], Reenu et al [2013], Sun et al [2018], Wang et al [2004], Gao et al [2018], Sellahewa and Jassim [2010], Guan et al [2017], Martini et al [2012].…”
Section: Introductionmentioning
confidence: 99%