Accession Number : ADA601950


Title :   Textile Fingerprinting for Dismount Analysis in the Visible, Near, and Shortwave Infrared Domain


Descriptive Note : Master's thesis


Corporate Author : AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT


Personal Author(s) : Yeom, Jennifer S


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a601950.pdf


Report Date : Mar 2014


Pagination or Media Count : 96


Abstract : The ability to accurately and quickly locate an individual, or a dismount, is useful in a variety of situations and environments. A dismount's characteristics such as their gender, height, weight, build, and ethnicity could be used as discriminating factors. Hyperspectral imaging (HSI) is widely used in e orts to identify materials based on their spectral signatures. More speci cally, HSI has been used for skin and clothing classi cation and detection. The ability to detect textiles (clothing) provides a discriminating factor that can aid in a more comprehensive detection of dismounts. This thesis demonstrates the application of several feature selection methods (i.e., support vector machines with recursive feature reduction, fast correlation based lter) in highly dimensional data collected from a spectroradiometer. The classi cation of the data is accomplished with the selected features and arti cial neural networks. A model for uniquely identifying ( ngerprinting) textiles are designed, where color and composition ard deternimed in order to ngerprint a speci c textile. An arti cial neural network is created based on the knowledge of the textile's color and composition, providing a uniquely identifying ngerprinting of a textile. Results show 100% accuracy for color and composition classi cation, and 98% accuracy for the overall textile ngerprinting process.


Descriptors :   *IDENTIFICATION , *SURFACE TARGETS , *TEXTILES , ACCURACY , CLASSIFICATION , COLORS , DETECTION , FABRICS , HEIGHT , HYPERSPECTRAL IMAGERY , NEURAL NETS , SEARCH AND RESCUE , SIZES(DIMENSIONS) , SURVEILLANCE , THESES , WEIGHT


Subject Categories : Textiles


Distribution Statement : APPROVED FOR PUBLIC RELEASE