VLSI Implementation of Object-Detection Design using Adaptive Block Partition Decision Algorithm

In this paper, an adaptive block partition decision methodology is presented for VLSI implementation of objectdetection for real-time ultra-high-definition (4K2K) resolution video displaying. The proposed adaptive block partition decision (ABPD) algorithm includes a data controller, a gray-level generator, a sub-block difference module, and an edge detector. The edge detector is designed for discovering edges in images using an efficient edgecatching 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 6.99K 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 increase the processing throughput, and accuracy of objetdetection for real-time