A study on PRNU-based source device identification for digital images and videos of different resolutions

Öz

PRNU (Photo Response Non-Uniformity), a noise pattern unique to each camera sensor, is one of the critical tools exploited for the forensic analysis of digital images and videos. Source camera attribution, the most widespread application of PRNU, is based on distinctive PRNU characteristics even of the same brand and model cameras and the inherent integration of this pattern into each exposed image or video frame as a camera fingerprint. It can be discovered whether a suspected camera may be the source of a query image or video based on a similarity test between the PRNU noise estimated from the query image/video and the reference PRNU of the camera that can be obtained accurately from a set of still-scene, e.g., wall or sky, images. In contrast to the images, low-quality encoding of digital video frames affects the accuracy of the estimated PRNU noise from video and hence of the similarity analysis. In this context, it may be wise to obtain the reference PRNU from images rather than videos for performance efficiency when working with source camera attribution for videos. However, images and videos are recorded in different aspect ratios and/or resolutions even though they are shot with the same source camera. Therefore, the reference PRNU obtained through images should be converted to the form corresponding to the same photosensitive cells as the query video PRNU noise. This paper proposes a technique to precisely estimate the scaling and cropping parameters leading to this geometric conversion.

Anahtar Kelimeler

• PRNU
• Source camera identification
• Image and video forensics

Farklı çözünürlükteki sayısal imge ve videolar için PRNU tabanlı kaynak kamera tespiti üzerine bir çalışma

Öz

Her bir kamera sensörüne has benzersiz bir gürültü bileşeni olan PRNU (Photo Response Non-Uniformity), sayısal imge ve videoların adli analizi kapsamında ihtiyaç duyulan önemli araçlardandır. PRNU’nun en yaygın uygulama alanı olan kaynak kamera tespiti, aynı marka ve model kameraların bile PRNU karakteristiğinin birbirinden farklı oluşu ve bu örüntünün çekilen her bir resim karesi üzerine bir kamera parmak izi gibi istemsiz eklenmesi esasına dayanmaktadır. Bir test dosyasından (imge ya da video) kestirimi sağlanan PRNU sensör gürültüsü ile dosyanın kaynağı olduğu düşünülen kameraya ait referans PRNU (sabit içerikli düz duvar ya da gökyüzü görüntülerinden yüksek doğrulukta elde edilen PRNU örüntüsü) arasındaki benzerliğe göre bu kameranın test videosunun kaynağı olup olamayacağı belirlenebilir. Sayısal video çerçevelerinin imgelere göre düşük kalitede kodlanması, videolardan kestirilen PRNU sensör gürültüsünün doğruluğunu, dolayısıyla da benzerlik analizini etkilemektedir. Bu bağlamda, videolarda PRNU tabanlı kaynak kamera tespitinde, referans PRNU’nun videolardansa imgelerden elde edilmesi performans etkinliği için önemli bir hamledir. Ancak, imge ve videolar aynı kaynak kamera ile çekilmiş olsalar dahi farklı en boy oranında ve/veya çözünürlükte kaydedilmektedirler. Bu sebeple, imgelerden elde edilen PRNU izinin, sorgu videosuna ait PRNU sensör gürültüsü ile aynı foto-alıcı hücrelere karşılık gelecek forma dönüştürülmesi gerekmektedir. Bu çalışmada, bu dönüşümü sağlayan ölçekleme ve kırpma parametrelerini hassas bir şekilde hesaplayabilen bir yöntem önerilmiştir.

Anahtar Kelimeler

• PRNU
• Kaynak kamera tespiti
• İmge ve videoların adli analizi

Kaynakça

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