We discuss dual-band infrared (DBIR) capabilities for imaging buried object sites. We identify physical features affecting thermal contrast needed to distinguish buried object sites from undisturbed sites or surface clutter. Apart from atmospheric transmission and system performance, these features include: object size, shape, and burial depth; ambient soil, disturbed soil and object site thermal diffusivity differences; surfe temperature, emissivity, plant-cover, slope, albedo and roughness variations; weather conditions and measurement times. We use ground instrumentation to measure the time-varying temperature differences between buried object sites and undisturbed soil sites. We compare near surface soil temperature differences with radiometric infrared (IR) surface temperature differences recorded at 4.7 0.4 .tm and at 10.6 1.0 jim. By producing selective DBIR image ratio maps, we distinguish temperature-difference patterns from surface emissivity effects. We discuss temperature differences between buried object sites, filled hole sites (without buried objects), cleared (undisturbed) soil sites, and grass-covered sites (with and without different types of surface clutter). We compare temperature, emissivity-ratio, visible and near-JR reflectance signatures of surface objects, leafy plants and sod. We discuss the physical aspects of environmental, surface and buried target features affecting interpretation of buried targets, surface objects and natural backgrounds.

In this paper, a new method to deal with automatic speaker verification based on band-limited phaseonly correlation (BLPOC) is proposed. The aim of this study is to validate the use of the BLPOC function as a new limited-data automatic speaker verification technique. Although some speaker verification techniques have high accuracy, efficiency usually depends on the extraction of complex theoretical information from speech signals and the amount of the data for training the algorithms. The BLPOC function is a high-accuracy biometric technique traditionally implemented in human identification by fingerprints (through image-matching). When applying the BLPOC function in automatic speaker verification through the proposed algorithms (under limited-data conditions), a 98.24% true acceptance rate (TAR) and 87.17% true rejection rate (TRR) in a custom database (and 93.75% TAR and 67.05% TRR in the ELSDSR database) were obtained. The proposed algorithm is a theoretically simple method for automatic speaker verification whose main advantage is that it can provide identification under limited-data conditions. In this sense, the BLPOC function could be applicable in other limited-data biometric identifications by sound signals.

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