The use of multidimensional perceptual models in the selection of sonar echo features.

The development of an accurate and efficient sonar-target classification system depends upon the identification of a set of signal features which may be used to discriminate important classes of signals. Feature selection can be facilitated through the identification of perceptual features used by human listeners in discriminating relevant sonar echoes. This study was conducted to establish a more reliable means of identifying perceptual features in terms of physical signal parameters as an initial step toward the development of an automatic sonar-target classification system. The results of an experiment involving eight subjects and six sonar echoes are presented. A model of the perceptual structure of these echoes was derived from subject similarity judgments using a multidimensional scaling (MDS) technique. It was found that three perceptual features accounted for the similarity judgments made by the human listeners. Echoes modified along candidate physical dimensions were employed to aid in the identification of perceptual dimensions in terms of physical signal parameters. The three perceptual features could be associated with signal parameters involving the amplitude envelope of the echoes.

Moiré inspection of multicomponent assemblies.

This paper discusses the use of moiré techniques to enhance optically the generation of binary images in automatic visual inspection systems. Techniques for enhancing the illumination of out-of-plane features or highlighting areas of missing or misaligned parts on an assembly were investigated. The applications of these techniques to a practical inspection problem were demonstrated.