基于硬件SURF算法的自校准双目测距系统

为了解决被动式双目测距系统中双目摄像头光轴对准误差较大、图像匹配精确度较低、计算速度慢等问题，提出了一种基于硬件加速稳健特征（SURF）算法的自校准双目测距系统。该方案采用位置敏感探测器与伺服电机作为双目摄像头光轴自校准平台，利用Zynq SoC处理器对SURF算法进行硬件加速，以实现两幅图像的特征匹配，从而达到精确、有效、自主的被动测距效果。实验表明本文方案采用位置敏感探测器可以有效地校准双目摄像头至同一平面位置，同时硬件SURF算法匹配图像的精确度高，速度快，满足被动测距系统的需求。

Abstract

In order to solve the problems of binocular camera′s optical axis alignment error, low image matching accuracy, and insufficient computing speed in passive binocular ranging systems, a new self-calibrated binocular ranging system based on hardware speeded up robust features (SURF) algorithm is proposed. The scheme uses position sensitive detectors and servo motors as the self-calibrating platform of the binocular cameras, and Zynq SoC is utilized to achieve the hardware acceleration of the SURF algorithm and feature matching of two images. Finally accurate and effective passive ranging is realized. The results show that the position sensitive detector can effectively calibrate the binocular cameras to the same plane position, and the hardware SURF algorithm can match images with high accuracy and speed. The scheme meets the demand of passive ranging systems.

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蒋晓东, 于纪言, 朱立坤, 黄建森. 基于硬件SURF算法的自校准双目测距系统[J]. 光学学报, 2018, 38(10): 1036001. Jiang Xiaodong, Yu Jiyan, Zhu Likun, Huang Jiansen. Self-Calibrated Binocular Ranging System Based on Hardware SURF Algorithm[J]. Acta Optica Sinica, 2018, 38(10): 1036001.

基于硬件SURF算法的自校准双目测距系统

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