Abstract

In this paper, an adaptive block partition decision methodology is presented for very large-scale integration (VLSI) implementation of object-detection for real-time ultrahigh-definition (4K2K) resolution video displaying. The proposed adaptive block partition decision algorithm includes a data controller, a gray-level generator, a subblock difference module, and an edge detector. The edge detector is designed for discovering edges in images using an efficient edge-catching technique. An adaptive block partition decision technique was added to enhance the shapes of objects and to decrease the edge distortion effects. Furthermore, a threshold constraint is used to set parameters for different sizes of blocks. A statistic methodology of object detection is also used to determine whether it is necessary to trigger an alert signal or not. The VLSI architecture of the proposed design contains 6.99-K gate counts. Its power consumption is 1.63 mW and its operating frequency is to 374.5 MHz by using a 90-nm CMOS technology. Compared with previous designs, the proposed design not only achieves reduction of more silicon area, but also increases the processing throughput, and accuracy of object-detection for real-time video display.

© 2016 IEEE

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