首页|School of Engineering and Sciences Researchers Describe Recent Advances in Intel ligent Systems (A novel indexing algorithm for latent palmprints leveraging minu tiae and orientation field)
School of Engineering and Sciences Researchers Describe Recent Advances in Intel ligent Systems (A novel indexing algorithm for latent palmprints leveraging minu tiae and orientation field)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Researchers detail new data in intelligent system s.According to news reporting from Estado de Mexico,Mexico,by NewsRx journali sts,research stated,"Latent palmprints represent crucial forensic evidence in criminal investigations,necessitating their storage in governmental databases." Financial supporters for this research include Universidad Autonoma De Madrid; C onsejo Nacional De Ciencia Y Tecnologia.The news reporters obtained a quote from the research from School of Engineering and Sciences:"The identification of corresponding palmprints within large-scal e databases using an automated palmprint identification system (APIS) is time-co nsuming and computationally intensive.To address this challenge,this paper int roduces an innovative approach:delineating the region of interest (ROI) for pal mprint segmentation and presenting a novel indexing algorithm founded on minutia e and the orientation field (OF).Additionally,a novel feature vector is propos ed,leveraging minutiae triplets and ellipse properties,marking the pioneering algorithm to consider minutiae importance in palmprint indexing.Significantly,an improved version of an existing palmprint indexing algorithm tailored for lat ent palmprints is introduced.The study demonstrates the indexing and retrieval of both our feature vectors and those obtained by the improved palmprint indexin g algorithm,using two clustering algorithms and locality-sensitive hashing (LSH ).The method's robustness is evaluated across three diverse databases with exte nsive palmprint records." According to the news editors,the research concluded:"The experimental results underscore the superior performance of our approach compared to current state-o f-the-art algorithms."
School of Engineering and SciencesEsta do de MexicoMexicoNorth and Central AmericaAlgorithmsIntelligent SystemsMachine Learning
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