A Descriptor based on Intensity Binning for Image Matching
B. Balasanjeevi, Chigurupalli Chandra Sekhar · 2014
This paper proposes a method for extracting image descriptors using intensity binning. It is based on the fact that, when the intensities of the interest regions are quantized, the pixels retain their bin labels under common image deformations, up to a certain degree of perturbation. Consequently, the spatial configuration and the shape of the connected regions of pixels belonging to each bin become resilient to noise, which, as a whole, capture the topography of the intensity map pertaining to that region. We examine the effect of classical image deformations on this representation and seek to find a compact yet robust representation which remains unperturbed in the presence of noise and image deformations. We use Oxford dataset in our experiments and the results show that the proposed descriptor gives a better performance than the existing methods for matching two images under common image deformations.