Enhancing Cold Cases Forensic Identification with DCGAN-based Personal Image Reconstruction

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dc.contributor.authorAL-Muttairi, Hasan Sabah K.
dc.contributor.authorKurnaz, Sefer
dc.contributor.authorAljuboori, Abbas Fadhil
dc.date.accessioned2025-07-03T07:20:33Z
dc.date.available2025-07-03T07:20:33Z
dc.date.issued2025
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalı
dc.description.abstractWith the improvement of artificial intelligence and deep learning techniques, especially deep convolutional generative adversarial network (DCGAN), there has been a significant development in personal identity and generating images through facial reconstruction systems. This study focuses on proposing a model of personal image reconstruction from forensic sketches using DCGAN. The model comprises two networks: a generator to convert sketch images into real images and a feature network to determine the similarity of the generated images to real ones. Forensic sketches provided by relevant authorities are used as inputs to the proposed model. These sketches include details and information on the perpetrators or missing persons obtained from witnesses or the missing person parents. Prominent facial features extracted from the reconstructed images aid in the process of personal image reconstruction. The proposed model shows good results, achieving up to 99% accuracy in the generated images. The error ratio is reported to be as low as 0.92% based on the evaluation using the CUHKFaces dataset. This study presents a new approach to reconstructing human face images from forensic sketches using DCGAN.
dc.identifier.citationAL-Muttairi, H. S. K., Kurnaz, S., & Aljuboori, A. F. (2025). Enhancing Cold Cases Forensic Identification with DCGAN-based Personal Image Reconstruction. Baghdad Science Journal, 22(2), 730-739. 10.21123/bsj.2024.10896
dc.identifier.doi10.21123/bsj.2024.10896
dc.identifier.endpage739
dc.identifier.issn2078-8665
dc.identifier.issn2411-7986
dc.identifier.issue2
dc.identifier.scopus2-s2.0-105001188446
dc.identifier.scopusqualityQ1
dc.identifier.startpage730
dc.identifier.urihttps://hdl.handle.net/20.500.12939/5787
dc.identifier.volume22
dc.identifier.wosWOS:001451260200029
dc.identifier.wosqualityQ2
dc.indekslendigikaynakScopus
dc.institutionauthorAL-Muttairi, Hasan Sabah K.
dc.institutionauthorKurnaz, Sefer
dc.language.isoen
dc.publisherUniversity of Baghdad
dc.relation.ispartofBaghdad Science Journal
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Öğrenci
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectDCGAN
dc.subjectDeep learning
dc.subjectForensic image reconstructing
dc.subjectpix2pix translation
dc.subjectSketch-to-image
dc.titleEnhancing Cold Cases Forensic Identification with DCGAN-based Personal Image Reconstruction
dc.title.alternativeالشخصیة المستندة إلى DCGAN تعزیز التعتعزیز التعرف على الحالات الباردة بالطب الشرعي من خلال إعادة بناء الصورة DCGAN الشخصیة المستندة إلىرف على الحالات الباردة بالطب الشرعي من خلال إعادة بناء الصورة
dc.typeArticle

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