Image retrieval based on multidimensional feature properties
Yew Hock Ang, Zhenyu Li, Sim Heng Ong · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
In this paper, multidimensional feature measures of object shapes and feature blobs for retrieval of ceramic artifacts (e.g., plates, vases, and bowls) are proposed. These measures capture the various granularity of image features necessary for representation of complex image objects and their painted designs. Object shape is characterized by region compactness, boundary eccentricity, region moment, and region convexity. High detailed regions are characterized by blob properties such as total blob size, number of blobs, dispersion of blobs, and central moment of blobs. Each set of multiple feature measures jointly forms a 4- dimensional feature vector in a multidimensional feature space. Feature abstraction of complex image details is further improved by the computing feature measurements on sub-resolution images. This allows features of different perceptual scales to be isolated and efficiently abstracted. We have applied our method of image content analysis for retrieval of ceramic artifacts and have shown that multiresolution multidimensional feature measures can adequately retrieve images with high perceptual similarity.