TY - GEN
T1 - Real-time texture extraction based on the improved median robust extended local binary pattern
AU - Wang, Mengnan
AU - Zhang, Yanjun
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/10/30
Y1 - 2020/10/30
N2 - Local binary patterns (LBP) are considered as the most computation efficient and high-performance texture features. Among all variants of the LBPs, Median Robust Extended Local Binary Pattern (MRELBP) [1] is considered as one of the highest-performance one. Based on the MRELBP, this paper proposes an improved real-time texture extraction architecture implemented on a field-programmable gate array (FPGA) device. The fixed-point fraction is used to replace the double float-point fraction, only results in less than 1% difference to the accuracy. The proposed system is implemented on Xilinx Zynq-7045, and the extraction time is linear with the size of the input image. The extraction time of the 128x128 image in the dataset Outex-TC is merely 85.64μs, which is more than 4800 times faster than Liu et al. implemented on MATLAB [2].
AB - Local binary patterns (LBP) are considered as the most computation efficient and high-performance texture features. Among all variants of the LBPs, Median Robust Extended Local Binary Pattern (MRELBP) [1] is considered as one of the highest-performance one. Based on the MRELBP, this paper proposes an improved real-time texture extraction architecture implemented on a field-programmable gate array (FPGA) device. The fixed-point fraction is used to replace the double float-point fraction, only results in less than 1% difference to the accuracy. The proposed system is implemented on Xilinx Zynq-7045, and the extraction time is linear with the size of the input image. The extraction time of the 128x128 image in the dataset Outex-TC is merely 85.64μs, which is more than 4800 times faster than Liu et al. implemented on MATLAB [2].
KW - Feature extraction
KW - Field-Programmable Gate Array (FPGA)
KW - MRELBP
KW - Real-time
UR - http://www.scopus.com/inward/record.url?scp=85099887589&partnerID=8YFLogxK
U2 - 10.1145/3436369.3436371
DO - 10.1145/3436369.3436371
M3 - Conference contribution
AN - SCOPUS:85099887589
T3 - ACM International Conference Proceeding Series
SP - 280
EP - 287
BT - ICCPR 2020 - Proceedings of 2020 9th International Conference on Computing and Pattern Recognition
PB - Association for Computing Machinery
T2 - 9th International Conference on Computing and Pattern Recognition, ICCPR 2020
Y2 - 30 October 2020 through 1 November 2020
ER -