Deep Image Orientation Angle Detection
This addresses the challenge of automatic image orientation correction for general users, but it is incremental as it builds on existing CNN methods.
The paper tackled the problem of estimating and rectifying image orientation angles by combining a CNN with a custom loss function, achieving state-of-the-art results for angles from 0 to 360 degrees.
Estimating and rectifying the orientation angle of any image is a pretty challenging task. Initial work used the hand engineering features for this purpose, where after the invention of deep learning using convolution-based neural network showed significant improvement in this problem. However, this paper shows that the combination of CNN and a custom loss function specially designed for angles lead to a state-of-the-art results. This includes the estimation of the orientation angle of any image or document at any degree (0 to 360 degree),