Detection of salient image points using principal subspace manifold structure

This paper presents a method to find salient image points in images with regular patterns based on deviations from the overall manifold structure. The two main contributions are that: (i) the features to extract salient point are derived directly and in an unsupervised manner from image neighborhoods, and (ii) the manifold structure is utilized, thus avoiding the assumption that data lies in clusters and the need to do density estimation. We illustrate the concept for the detection of fingerprint minutiae, fabric defects, and interesting regions of seismic data.