We show that changes to the color distribution statistics induced by resampling operations on color images present useful features for the detection and estimation of embeddings due to LSB steganography. The resampling operations considered in our study are typical operations like zoom-in, zoom-out, rotations and distortions. We show experimental evidence that the features computed from these resampling operations form distinct clusters in pattern space for different levels of embeddings and are amenable to classification using a pattern classifier like SVM. Our method works well not only for LSB Replacement Steganography but also for the LSB Matching approach.