Abstract
Image similarity search is crucial in various applications. Determining similarities among objects of images is a key point of perceptual image resemblance. Identification of varied pose of human face is the biggest issue under image resemblance. Mostly the previous research uses different distance metric algorithms to measure the image resemblance where the distance between two objects of images is used to determine the degree of resemblance. This paper presented a streamlined algorithm termed as Description Proximity Cover for computing the perceptual image resemblance based on neighborhoods. Comparative analysis of DPC has done with other existing metric based algorithms using large dataset of images. Further the resemblance of facial expression of images has also carried out using DPC. It has been found from the experimental results that retrieval performance may be significantly improved using Description Proximity Cover.
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