Content Based Image Retrieval using Wavelet Transforms with Dynamic Texture (DT)
In this paper, we address the problem of segmenting CBIR using Wavelet Transforms with a Dynamic Texture (DT) into disjoint regions. A DT might be different from its spatial mode (i.e., appearance - color variation) and/or temporal mode (i.e., motion field - movement of objects). For the appearance mode, we use a new local spatial texture descriptor to describe the spatial mode of the DT; for the motion mode, we use the optical flow and the local temporal texture descriptor to represent the temporal variations of the DT. In addition, for the optical flow, we use the histogram of oriented optical flow (HOOF) to organize them. To compute the distance between two HOOFs, we develop a simple effective and efficient distance measure based on Weber’s law. Furthermore, we also address the problem of threshold selection by proposing a method for determining thresholds for the segmentation method by an ofﬂine supervised statistical learning.
Keywords - 1. Content Based Image Retrieval, 2. Dynamic Texture (DT).