The range-gated imaging systems are reliable underwater imaging system with the capability to minimize backscattering effect from turbid media. The tail-gating technique has been developed to fine tune the signal to backscattering ratio and hence improve the gated image quality. However, the tail-gating technique has limited image quality enhancement in high turbidity levels. In this paper, we developed a numerical model of range-gated underwater imaging system for near target in turbid medium. The simulation results matched the experimental work favorably. Further investigation using this numerical model shows that the multiple scattering components of the backscattering noise dominate for propagation length larger than 4.2 Attenuation Length (AL). This has limited the enhancement of tail-gating technique in high turbidity conditions.

This paper performs an experimental investigation on the TOF imaging profile which strongly influences the quality of reconstruction to accomplish accurate range sensing. From our analysis, the reflected intensity profile recorded appears to deviate from Gaussian model which is commonly assumed and can be perceived as a mixture of noises and actual reflected signal. Noise-weighted Average range calculation is therefore proposed to alleviate noise influence based on the signal detection threshold and system noises. From our experimental result, this alternative range solution demonstrates better accuracy as compared to the conventional weighted average method and proven as a para-axial correction to improve range reconstruction in 3D gated imaging system.

Biometric template protection (BTP) schemes are implemented to increase public confidence in biometric systems regarding data privacy and security in recent years. The introduction of BTP has naturally incurred loss of information for security, which leads to performance degradation at the matching stage. Although efforts are shown in the extended work of some iris BTP schemes to improve their recognition performance, there is still a lack of a generalized solution for this problem. In this paper, a trainable approach that requires no further modification on the protected iris biometric templates has been proposed. This approach consists of two strategies to generate a confidence matrix to reduce the performance degradation of iris BTP schemes. The proposed binary confidence matrix showed better performance in noisy iris data, whereas the probability confidence matrix showed better performance in iris databases with better image quality. In addition, our proposed scheme has also taken into consideration the potential effects in recognition performance, which are caused by the database-associated noise masks and the variation in biometric data types produced by different iris BTP schemes. The proposed scheme has reported remarkable improvement in our experiments with various publicly available iris research databases being tested.

Iris has been found to be unique and consistent over time despite its random nature. Unprotected biometric (iris) template raises concerns in security and privacy, as numerous large-scale iris recognition projects have been deployed worldwide—for instance, susceptibility to attacks, cumbersome renewability, and cross-matching. Template protection schemes from biometric cryptosystems and cancelable biometrics are expected to restore the confidence in biometrics regarding data privacy, given the great advancement in recent years. However, a majority of the biometric template protection schemes have uncertainties in guaranteeing criteria such as unlinkability, irreversibility, and revocability, while maintaining significant performance. Fuzzy commitment, a theoretically secure biometric key binding scheme, is vulnerable due to the inherent dependency of the biometric features and its reliance on error correction code (ECC). In this paper, an alignment-free and cancelable iris key binding scheme without ECC is proposed. The proposed system protects the binary biometric data, i.e., IrisCodes, from security and privacy attacks through a strong and size varying non-invertible cancelable transform. The proposed scheme provides flexibility in system storage and authentication speed via controllable hashed code length. We also proposed a fast key regeneration without either re-enrollment or constant storage of seeds. The experimental results and security analysis show the validity of the proposed scheme.