Feature Extraction and Selection From the Perspective of Explosive Detection

摘要

Features are extractable measurements from a sample image summarizing the information content in an image and in the process providing an essential tool in image understanding. In particular, they are useful for image classification into pre-defined classes or grouping a set of image samples (also called clustering) into clusters with similar within-cluster characteristics as defined by such features. At the lowest level, features may be the intensity levels of a pixel in an image. The intensity levels of the pixels in an image may be derived from a variety of sources. For example, it can be the temperature measurement (using an infra-red camera) of the area representing the pixel or the X-ray attenuation in a given volume element of a 3-d image or it may even represent the dielectric differential in a given volume element obtained from an MIR image.