Robust template feature matching method using motion-constrained DCF designed for visual navigation in asteroid landing

A robust and eficient feature matching method is necessary for visual navigation in asteroid-landing missions.Based on the visual navigation framework and motion characteristics of asteroids,a robust and efficient template feature matching method is proposed to adapt to feature distortion and scale change cases for visual navigation of asteroids.The proposed method is primarily based on a motion-constrained discriminative correlation filter(DCF).The prior information provided by the motion constraints between sequence images is used to provide a predicted search region for template feature matching.Additionally,some specific template feature samples are generated using the motion constraints for correlation filter learning,which is beneficial for training a scale and feature distortion adaptive correlation filter for accurate feature matching.Moreover,average peak-to-correlation energy(APCE)and jointly consistent measurements(JCMs)were used to eliminate false matching.Images captured by the Touch And Go Camera System(TAGCAMS)of the Bennu asteroid were used to evaluate the performance of the proposed method.In particular,both the robustness and accuracy of region matching and template center matching are evaluated.The qualitative and quantitative results illustrate the advancement of the proposed method in adapting to feature distortions and large-scale changes during spacecraft landing.

Facial Index Based 2D Facial Composite Process for Forensic Investigation in Sri Lanka

The “facial composite” is one of the major fields in the forensic science that helps the criminal investigators to carry out their investigation process. The survey conducted by United States Law Enforcement Agencies confirms that 80% of the law enforcement agencies use computer automated composite systems whereas Sri Lanka is still far behind in the process of facial composite with lot of inefficiencies in the current manual process. Hence this research introduces a novel approach for the manual facial composite process, while eliminating the inefficiencies of the manual procedure in Sri Lanka. In order to overcome this situation, this study introduces an automated image processing based software solution with 2D facial feature templates targeting the Sri Lankan population. Thus, this was the first ever approach that creates the 2D facial feature templates by incorporating both medically defined indexes and relevant aesthetic aspects. Hence, this research study is comprised of two separate analyses on anthropometric indices and facial feature shapes which were carried out targeting the local population. Subsequently, several evaluation techniques were utilized to evaluate this methodology where we obtained an overall success rate as 70.19%. The ultimate goal of this research study is to provide a system to the law enforcement agencies in order to carry out an efficient and effective facial composite process which can lead to increase the success rate of suspect identification.