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Bit-Plane Extracted Moving-Object Detection Using Memristive Crossbar-CAM Arrays for Edge Computing Image Devices

In this paper, we present the hardware implementation of a novel algorithm for moving-object detection, which can be integrated with CMOS image sensors. Bit planes of consecutive frames are stored… Click to show full abstract

In this paper, we present the hardware implementation of a novel algorithm for moving-object detection, which can be integrated with CMOS image sensors. Bit planes of consecutive frames are stored in memristive crossbar arrays and compared using threshold-logic XOR gates. The resulting outputs are combined using weighted summation circuits and thresholded using comparators, to obtain binary images. A resistive content-addressable memory (CAM) array is used in the output stage to observe the numbers of different object pixels in the first and second pairs of the processed frames, in a row-by-row manner. The CAM array output conveys information on the motion direction and allows for optimal memory utilization through the selective row-wise storage of different bits. The proposed method outperforms the conventional moving-object detection algorithms, in terms of accuracy, specificity, and positive prediction metrics, and performs comparably in terms of other metrics.

Keywords: object detection; memristive crossbar; image; moving object

Journal Title: IEEE Access
Year Published: 2018

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