A new RGB based fusion for forged IMEI number detection in mobile images
Document Type
Conference Article
Publication Title
Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR
Abstract
As technology advances to make living comfortable for people, at the same time, different crimes also increase. One such sensitive crime is creating fake International Mobile Equipment Identity (IMEI) for smart mobile devices. In this paper, we present a new fusion based method using R, G and B color components for detecting forged IMEI numbers. To the best of our knowledge, this is the first work for forged IMEI number detection in mobile images. The proposed method first finds variances for R, G and B images of a forged input image to study local changes. The variances are used to derive weights for respective color components. The same weights are convolved with respective pixel values of R, G and B components, which results in the fused image. For the fused image, the proposed method extracts features based on sparsity, the number of connected components, and the average intensity values for edge components in respective R, G and B components, which gives six features. The proposed method finds absolute difference between fused and input images, which gives feature vector containing six difference values. The proposed method constructs templates based on samples chosen randomly. Feature vectors are compared with the templates for detecting forged IMEI numbers. Experiments are conducted on our own dataset and standard datasets to evaluate the proposed method. Furthermore, comparative studies with the related existing methods show that the proposed method outperforms the existing methods.
First Page
386
Last Page
391
DOI
10.1109/ICFHR-2018.2018.00074
Publication Date
12-5-2018
Recommended Citation
Shivakumara, Palaiahnakote; Basavaraja, V.; Gowda, Harsha S.; Guru, D. S.; Pal, Umapada; and Lu, Tong, "A new RGB based fusion for forged IMEI number detection in mobile images" (2018). Conference Articles. 29.
https://digitalcommons.isical.ac.in/conf-articles/29