| Citation: | WANG Peng, CAO Yunfeng, XU Lei, et al. SoC collaborative acceleration design method for image scaling algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(2): 333-339. doi: 10.13700/j.bh.1001-5965.2018.0313(in Chinese)
|
Aimed at the problem that a large number of images need to be scaled in the visual algorithm for the runway detection, recognition and tracking of the unmanned aerial vehicle with high real-time requirement, a new image scaling algorithm suitable for hardware acceleration is proposed based on the mapping relation of the input-output pixel. By simplifying the algorithm structure and using the field programmable gate array to design the hardware function of the module, the algorithm accelerates, and the real-time image processing system is built by the software and hardware cooperative architecture. The experimental results show that the improved scaling algorithm has high precision and less time consumption, and it can speed up by 171 times with the hardware logic. The hardened system can get the image data through the camera, and the real-time processing is displayed in the monitor, which has 30 frame/s processing speed. It can be applied to the image processing algorithm with high real-time requirement.
| [1] |
RETTKOWSKI J, BOUTROS A, GOHRINGER D.HW/SW co-design of the HOG algorithm on a Xilinx Zynq SoC[J]. Journal of Parallel and Distributed Computing, 2017, 109(1):50-62. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=893c1fba8b2068f9cb7fc078d4303e3d
|
| [2] |
KRYJAK T, KOMORKIEWICZ M, GORGON M.Real-time hardware-software embedded vision system for its smart camera implemented in Zynq SoC[J]. Journal of Real-Time Image Processing, 2016, 12(4):1-37. doi: 10.1007/s11554-016-0588-9
|
| [3] |
SENOUCI B, CHARFI I, HEYRMAN B, et al.Fast prototyping of a SoC-based smart-camera:A real-time fall detection case study[J]. Journal of Real-Time Image Processing, 2016, 12(4):649-662. doi: 10.1007/s11554-014-0456-4
|
| [4] |
SVETEK A, BLAKE M, HERMIDA M C, et al.The calorimeter trigger processor card:The next generation of high speed algorithmic data processing at CMS[J]. Journal of Instrumentation, 2016, 11(2):201-210. http://adsabs.harvard.edu/abs/2016JInst..11C2011S
|
| [5] |
ZARANDY A, NEMETH M, NAGY Z, et al.A real-time multi-camera vision system for UAV collision warning and navigation[J]. Journal of Real-Time Image Processing, 2016, 12(4):709-724. doi: 10.1007/s11554-014-0449-3
|
| [6] |
刘镇弢, 李涛, 黄虎才, 等.一种用于实时图像处理的众核结构设计[J].西安电子科技大学学报, 2015, 42(2):95-101. doi: 10.3969/j.issn.1001-2400.2015.02.016
LIU Z T, LI T, HUANG H C, et al.A design of the core structure for real-time image processing[J]. Journal of Xidian University, 2015, 42(2):95-101(in Chinese). doi: 10.3969/j.issn.1001-2400.2015.02.016
|
| [7] |
杨帆, 张皓, 马新文, 等.基于FPGA的图像处理系统[J].华中科技大学学报(自然科学版), 2015, 43(2):119-123. http://d.old.wanfangdata.com.cn/Thesis/Y1172118
YANG F, ZHANG H, MA X W, et al.Image processing system based on FPGA[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition), 2015, 43(2):119-123(in Chinese). http://d.old.wanfangdata.com.cn/Thesis/Y1172118
|
| [8] |
ZHAI X, ALI A S, AMIRA A, et al.MLP neural network based gas classification system on Zynq SoC[J]. IEEE Access, 2016, 4(2):8138-8146. http://ieeexplore.ieee.org/document/7605493/
|
| [9] |
HAN Y, VIRUPAKSHAPPA K, VITORSILVAPINTO E, et al.Hardware/software co-design of a traffic sign recognition system using Zynq FPGAs[J]. Electronics, 2015, 4(4):1062-1089. doi: 10.3390/electronics4041062
|
| [10] |
KELLY C, SIDDIQUI F M, BARDAK B, et al.FPGA soft-core processors, compiler and hardware optimizations validated using HOG[C]//International Symposium on Applied Reconfigurable Computing.Berlin: Springer, 2016, 1: 78-90.
|
| [11] |
ALTUNCU M A, GUVEN T, BECERIKLI Y, et al.Real-time system implementation for image processing with hardware/software co-design on the Xilinx Zynq platform[J]. International Journal of Information and Electronics Engineering, 2015, 5(6):473-477. doi: 10.7763/IJIEE.2015.V5.582
|
| [12] |
KRAJNIK T, SVAB J, PEDRE S, et al.FPGA-based module for SURF extraction[J]. Machine Vision and Applications, 2014, 25(3):787-800. doi: 10.1007/s00138-014-0599-0
|
| [13] |
GAO F, HUANG Z, WANG S, et al.Optimized parallel implementation of face detection based on embedded heterogeneous many-core architecture[J]. International Journal of Pattern Recognition and Artificial Intelligence, 2017, 31(7):175-180. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=10.1142_S0218001417560110
|
| [14] |
ISHIKAWA S, TAKAHASHI T, WATANABE S, et al.High-speed X-ray imaging spectroscopy system with Zynq SoC for solar observations[J]. Nuclear Instruments and Methods in Physics Research Section A:Accelerators, Spectrometers, Detectors and Associated Equipment, 2017, 22(1):40-52. http://arxiv.org/abs/1711.04372
|
| [15] |
CAI W, XU Z, LI Z.A high performance surf image feature detecting system based on Zynq[J]. DEStech Transactions on Computer Science and Engineering, 2017, 11(2):101-110.
|
| [16] |
王博.数字图像缩放及其质量评价方法研究[D].哈尔滨: 哈尔滨工程大学, 2015: 97-105. http://cdmd.cnki.com.cn/Article/CDMD-10217-1017245829.htm
WANG B.Digital image zoom and its quality evaluation method[D]. Harbin: Harbin Engineering University, 2015: 97-105(in Chinese). http://cdmd.cnki.com.cn/Article/CDMD-10217-1017245829.htm
|
Figures(7) / Tables(3)
Copyright © Journal of Beijing University of Aeronautics and Astronautics
Address: Editorial Department of Journal of Beijing University of Aeronautics and Astronautics, 37 Xueyuan Road, Haidian District, Beijing Post Code: 100191 Email: jbuaa@buaa.edu.cn
Supported by:
Beijing Renhe Information Technology Co., Ltd.
DownLoad:
