In our previous papers, the FPGA-based processing package and the co-processor board have been introduced for numerous commercial and military applications including motion detection, optical flow, background velocimetry, and target tracking. The processing package is being continually upgraded by new point- and area-applied algorithms for a variety of real-time digital video camera systems including foveal sensors based on Nova's Variable Acuity Superpixel Imager (VASITM) and Large Format VASITM (LVASITM) technologies. This paper demonstrates the FPGA-based processor for high frame-rate target detection in a cluttered background using variable acuity sensors. For the 1024 x 1024 pixel LVASITM Focal Plane Array (FPA), the proposed target-detection algorithm increases the frame rate from 4 Hz for the full resolution mode up to 450 Hz for the foveal mode while maintaining full field of view and target-detection performances on cluttered backgrounds that are comparable with detection performances at the full resolution mode.
Nova Sensors produces miniature electronics for a variety of real-time digital video camera systems, including foveal sensors based on Nova's Variable Acuity Superpixel Imager (VASITM) technology. An advanced image-processing package has been designed at Nova Sensors to re-configure the FPGA-based co-processor board for numerous applications including motion detection, optical, background velocimetry and target tracking. Currently, the processing package consists of 14 processing operations that cover a broad range of point- and area-applied algorithms. Flexible FPGA designs of these operations and re-programmability of the processing board allows for easy updates of the VASITM sensors, and for low-cost customization of VASITM sensors taking into account specific customer requirements.
This paper describes the image processing algorithms implemented and verified in Xilinx FPGAs and provides the major technical performances with figures illustrating practical applications of the processing package.
Cyan Systems has developed algorithms and architectures capable of performing temporal and spatial filtering near or on the FPA. Cyan is performing research into more advanced techniques to allow functional target detection near/on the FPA. The goals of this work is to perform image processing near or on the FPA to improve the size and power requirements for existing IR sensor systems which require larger board sets and hardware enclosures. We use representations of the biological vision system as models for the algorithm development. We report measured data on the near/on FPA target detection performance.
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