Query by Image Examination: Classification of Digital Image-Based Forensics Using Deep Learning Methods

Authors : Ilker Kara

Pages : 348-359

Doi:10.26650/acin.1282567

View : 30 | Download : 128

Publication Date : 2023-12-29

Article Type : Research Paper

Abstract :The continuous increase in the use of information systems and online services has also spurred the forensic examination of digital and image data, which serves as the primary platform for information transfer. In particular, according to the latest reports, the examination of the images obtained from all kinds of recording devices that have the quality of evidence as a result of the forensic case and that can provide the clarification of the incident and the detection of the criminal elements are becoming a critical problem due to the huge amount of data. Our contribution in this study is two-folded. First, we present a new approach that classifies digital images into eight different crime categories using six different models. Second, we have created a new dataset for the classification of crimes and opened it to the public. Throughout the study, we have used our new dataset which has a total of 15,065 image samples from 8 different crime categories including Bet, ChildAbuse, Credit Card and Banking, Drugs, Frightening, Knives, Pornographic and Weapons. In this study, six different models were used to classify crime images. The CNN model was developed by us and five other models used for transfer learning. Pre-trained network model parameters VGG16, VGG19, Xception Model, InceptionResNetV2 and NASNetLarge were used for crime image classification tasks. In addition, the performance of these models is compared using test accuracy and time metrics. Resultly, we achieved prediction accuracy of up to 89.74% using the NASNetLarge model.
Keywords : Görüntü işleme, derin öğrenme yöntemi, görüntü sınıflandırması, veri madenciliği, adli inceleme