There are some cases where dissimilar images are judged to be similar in using quadratic-form distance, a representative one in similarity searches of images. To address this problem, we proposed a multi-vector feature space method based on pseudo-Euclidean space and an oblique basis (MVPO). In this method, an image is represented by a solid consisting of multiple vectors; each vector corresponds to each feature. We also proposed D-distance as a distance between solids. A representative method similar to ours is Earth Mover's Distance (EMD), which is said to experimentally outperforms others including quadratic-form distance in precision. We show that EMD can be formalized as a distance in MVPO, and a reason why it outperforms quadratic-form distance. We also mention the difference between D-distance and EMD.