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Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

Linear high-boost fusion of Stokes vector imagery for effect...

引用

Conference on Polarization - Measurement, Analysis, and Remote Sensing IX

作者： El-Saba, Aed Sakla, Wesam A. Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77840 USA

ISBN: (纸本)9780819481368

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

关键词： automatic target recognition decoys Stokes vector imagery high-boost fusion wavelet-filter joint transform correlation correlation performance metrics

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Improving the recognition of fingerprint biometric system using enhanced image fusion

Improving the recognition of fingerprint biometric system us...

引用

Conference on Mobile Multimedia/Image Processing, Security, and Applications 2010

作者： Alsharif, Salim El-Saba, Aed Stripathi, Reshma Univ S Alabama Dept Elect & Comp Engn Mobile AL 36688 USA

ISBN: (纸本)9780819481726

Fingerprints recognition systems have been widely used by financial institutions, law enforcement, border control, visa issuing, just to mention few. Biometric identifiers can be counterfeited, but considered more reliable and secure compared to traditional ID cards or personal passwords methods. Fingerprint pattern fusion improves the performance of a fingerprint recognition system in terms of accuracy and security. This paper presents digital enhancement and fusion approaches that improve the biometric of the fingerprint recognition system. It is a two-step approach. In the first step raw fingerprint images are enhanced using high-frequency-emphasis filtering (HFEF). The second step is a simple linear fusion process between the raw images and the HFEF ones. It is shown that the proposed approach increases the verification and identification of the fingerprint biometric recognition system, where any improvement is justified using the correlation performance metrics of the matching algorithm.

关键词： Biometric system image fusion high-frequency emphasis filtering wavelet-filter joint transform correlation fingerprint verification and identification

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