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Shamima A. Mitu

Publications and source records attributed to Shamima A. Mitu.

2 recordsLinked to original sources

Temporal Scale and Shift Invariant Automatic Event Recognition using the Mellin Transform

The Spatio-temporal holographic correlator combines the traditional 2D optical image correlation techniques with inhomogeneously broadened arrays of cold atoms to achieve 3D time-space correlation to realize automatic event recognition at an ultra-high speed. Here we propose a method to realize such event recognition for videos running at different speeds. With this method, we can highly improve recognition accuracy and filter almost all the unwanted events in the video database.

cs.CV

Ultra-fast Real-time Target Recognition Using a Shift, Scale, and Rotation Invariant Hybrid Opto-electronic Joint Transform Correlator

Hybrid Opto-electronic correlators (HOC) overcome many limitations of all-optical correlators (AOC) while maintaining high-speed operation. However, neither the OEC nor the AOC in their conventional configurations can detect targets that have been rotated or scaled relative to a reference. This can be addressed by using a polar Mellin transform (PMT) pre-processing step to convert input images into signatures that contain most of the relevant information, albeit represented in a shift, scale, and rotation invariant (SSRI) manner. The PMT requires the use of optics to perform the Fourier transform and electronics for a log-polar remapping step. Recently, we demonstrated a pipelined architecture that can perform the PMT at a speed of 720 frames per second (fps), enabling the construction of an efficient opto-electronic PMT pre-processor. Here, we present an experimental demonstration of a complete HOC that implements this technique to achieve real-time and ultra-fast SSRI target recognition for space situational awareness. For this demonstration, we make use of a modified version of the HOC that makes use of Joint Transform Correlation , thus rendering the system simpler and more compact.

physics.optics