Precise localization of key-points to identify local regions for robust data hiding
We propose a novel data hiding system where data is embedded in local non-overlapping regions in an image. To survive cropping, the encoder embeds the same data in multiple regions of fixed dimensions, while the decoder's challenge is to independently retrieve these regions. Salient feature points are computed on an image and the local regions are centered around them. To obtain non-overlapping regions, the points are pruned based on their corner strength and the size of the region. The decoder can retrieve the data only if it can precisely identify one or more of the same key-points. We present suitable key-point pruning methods such that even after considering a reduced number of key-points, the receiver is successful in identifying the same key-point locations as the encoder. We perform experimental comparison of various corner detectors and also study the performance of segmentation methods to obtain robust key-points.