Rotation and Illumination Invariant Interleaved Intensity Order-Based Local Descriptor

The region descriptors using local intensity ordering patterns have become more popular recent years for image matching due to its enhanced discriminative ability. However, the dimension of these descriptors increases rapidly with the slight increase in the number of local neighbors under consideration and becomes unreasonable for image matching due to time constraint. In this paper, we reduce the dimension of the descriptor and matching time significantly while keeping up the comparable performance by considering the number of neighboring sample points in an interleaved manner. The proposed interleaved order based local descriptor (IOLD) considers the local neighbors of a pixel as a set of interleaved neighbors and constructs the descriptor over each set separately and finally combines them to produce a single pattern. We extract the local ordering pattern to cope up with the illumination effect in an inherent rotation invariant manner. The novelty lies with using multiple neighboring sets in an interleaved fashion. We also explored the local intensity order pattern in a multisupport-region scenario. Results are compared over three challenging and widely adopted image matching data sets with other prominent descriptors under various image transformations. Results based on experiments suggest that the proposed IOLD descriptor outperforms in terms of both improved matching performance and reduced matching time. We also found that the amount of improvement is significant under complex illumination difference while showing more robustness toward noise.