Publications
2019
1.
Biswas, Rubel; González-Castro, Victor; Fidalgo, Eduardo; Chaves, Deisy
Boosting child abuse victim identification in Forensic Tools with hashing techniques Artículo de revista
En: V Jornadas Nacionales de Investigación en Ciberseguridad, vol. 1, pp. 344–345, 2019.
Resumen | Enlaces | BibTeX | Etiquetas: Child Sexual Abuse, CSA, Face Identification, Forensic Tools, Occluded Face Recognition, perceptual hashing
@article{biswas_boosting_2019,
title = {Boosting child abuse victim identification in Forensic Tools with hashing techniques},
author = {Rubel Biswas and Victor González-Castro and Eduardo Fidalgo and Deisy Chaves},
url = {https://d1wqtxts1xzle7.cloudfront.net/82369096/JNIC2019_paper_11-libre.pdf?1647729671=&response-content-disposition=inline%3B+filename%3DBoosting_child_abuse_victim_identificati.pdf&Expires=1739810458&Signature=AaFk3CnTgqPwNnr4OrQ5dsZkqjASKk7CkhuGAp8EOF-QuWpTRVAHTZT4xLl1lS1NbnaDHI9p6jPc9VBhUkfmf0tLOACFOMUePTJRQbAXBLbmVv6LRjudXB1eBxP-MFeBs5vE0Ok4QaUFalGTOmM6hBXQqZC1Wb5tMxsKZPEB8eI6SxboBVqqlinMT9wyAbjykITOSmqsRSTHjOH9vHL~SZ5-PuVIbmT82w7vTdnCvovPoSwA6rmGO~IICQINI0mvYiwRYtdYVDSodTg4W7WVfst3jrcVgK76BKJHYUnH6A1HqYO38mm0MEIeXmbTSpMERXAEkc2Ja-tnkB2pyUR-Mg__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA},
year = {2019},
date = {2019-01-01},
journal = {V Jornadas Nacionales de Investigación en Ciberseguridad},
volume = {1},
pages = {344–345},
abstract = {This work presents a new scheme for identifying occluded faces using perceptual image hashing, which differs from traditional methods by eliminating the need for prior training of a facial model. The proposed method combines frequency coefficients and statistical image information to enhance the recognition accuracy of occluded faces. The approach aims to improve face recognition in forensic applications, such as identifying victims in Child Sexual Abuse (CSA) materials. Experimental results demonstrate that the new method outperforms previous methods in occluded face identification using the LFW database.},
keywords = {Child Sexual Abuse, CSA, Face Identification, Forensic Tools, Occluded Face Recognition, perceptual hashing},
pubstate = {published},
tppubtype = {article}
}
This work presents a new scheme for identifying occluded faces using perceptual image hashing, which differs from traditional methods by eliminating the need for prior training of a facial model. The proposed method combines frequency coefficients and statistical image information to enhance the recognition accuracy of occluded faces. The approach aims to improve face recognition in forensic applications, such as identifying victims in Child Sexual Abuse (CSA) materials. Experimental results demonstrate that the new method outperforms previous methods in occluded face identification using the LFW database.