Predict the model of a camera
This work addresses camera model identification for forensic or security applications, but it appears incremental as it combines existing features and methods without novel breakthroughs.
The paper tackled the problem of predicting camera models from photographs by using Discrete Wavelet Domain and Local Binary Patterns features, and it applied Logistic regression, K-NN, and Artificial Neural Networks for classification without reporting specific performance numbers.
In this work we address the problem of predicting the model of a camera based on the content of their photographs. We use two set of features, one set consist in properties extracted from a Discrete Wavelet Domain (DWD) obtained by applying a 4 level Fast Wavelet Decomposition of the images, and a second set are Local Binary Patterns (LBP) features from the after filter noise of images. The algorithms used for classification were Logistic regression, K-NN and Artificial Neural Networks