A local-holistic graph-based descriptor for facial recognition

Metin Zontul

Face recognition remains critical and up-to-date due to its undeniable contribution to security. Many descriptors, the most vital figures used for face discrimination, have been proposed and continue to be done. This article presents a novel and highly discriminative identifier that can maintain high recognition performance, even under high noise, varying illumination, and expression exposure. By evolving the image into a graph, the feature set is extracted from the resulting graph rather than making inferences directly on the image pixels as done conventionally. The adjacency matrix is create ...Daha fazlası

Makale 2022 MULTIMEDIA TOOLS AND APPLICATIONS82 ( 13 ) , pp. 1 - 19298 179 Görüntülenme Süresiz Ambargo

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Facial Recognition in Hexagonal Domain-A Frontier Approach

Onur Osman

Many face-recognition (FR) methods have been proposed thus far. Although FR has achieved wisdom in square pixel-based image processing (SIP) due to many studies, this wisdom has not been transferred to Hexagonal pixel-based image processing (HIP) until now. This study presents HIP versions of the most basic texture extraction studies in SIP, namely Gray-Level-Co-occurrence-Matrices (GLCM), Local Binary Pattern (LBP), and our recent work, local-holistic graph-based descriptor (LHGPD). The images are first transformed from the SIP domain to the HIP domain. The HIP domain equivalences (HexGLCM, H ...Daha fazlası

Makale 2023 IEEE ACCESS 11 , pp. 4 - 46591 34 Görüntülenme