@inproceedings{b4a62ab218dd45a6b11351fe177887bf,
title = "An optimized FPGA implementation based on scale invariant feature transform feature points detection",
abstract = "Aiming at the characteristics of SIFT (Scale Invariant Feature Transform) algorithm which has large amount of calculation and can be highly paralleled, we propose an optimized FPGA implementation so that it can be accelerated on hardware. In this method, we firstly simplify the process of filtering image and generating Gaussian pyramids through selecting appropriate parameters and hardware structure, then use fixed-point decimals to increase the accuracy of operation, finally build feature detection module in a parallel way and make simulation and verification using different input images. Results of experiments show that, this method can significantly reduce the amount of calculation of the algorithm and save hardware resources with the premise of ensuring detection accuracy, which has a good performance.",
keywords = "FPGA, SIFT, accelerate, accuracy, simplify",
author = "Yue Gu and Xiujie Qu and Yue Sun and Liwen Gao and Shuang Yu",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016 ; Conference date: 13-08-2016 Through 15-08-2016",
year = "2016",
month = oct,
day = "19",
doi = "10.1109/FSKD.2016.7603266",
language = "English",
series = "2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "734--739",
editor = "Jiayi Du and Chubo Liu and Kenli Li and Lipo Wang and Zhao Tong and Maozhen Li and Ning Xiong",
booktitle = "2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016",
address = "United States",
}