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Real-time Hardware Implementation of Stereo Image Rectification with Calibrated Cameras

机译:使用校准相机的立体图像整流的实时硬件实现

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Nowadays stereo matching has been proved as a useful technique for acquiring depth information from stereo images. To reduce the computation cost of the matching process, image rectification is regarded as an essential step which horizontally aligns the objects in both images. However, it is still a challenge to reach good performance in both processing speed and rectification quality. In this paper, the whole rectification process can be divided into two phases, which are implemented by a core processor and dedicated hardware separately. A hardware architecture is proposed based on the rectification method. Furthermore, the architecture is optimized as a pipelined system to improve its processing ability. In the system which is implemented on an Altera FPGA, real-world images are captured by calibrated cameras as input, and rectified images of 1024 × 768 resolution are displayed as output at 60 frames per second (fps). The experimental results indicate that the rectified images have few pixels of vertical mismatches.
机译:如今,立体匹配被证明是从立体图像获取深度信息的有用技术。为了降低匹配过程的计算成本,将图像整流视为水平对准两个图像中的对象的基本步骤。但是,在处理速度和整改质量方面达到良好性能仍然是一项挑战。在本文中,整个整流过程可分为两个阶段,其由核心处理器和专用硬件分开实现。基于整流方法提出了硬件架构。此外,该体系结构被优化为流水线系统,以改善其处理能力。在系统上在Altera FPGA实现的系统中,通过校准的相机作为输入捕获实际图像,并且1024×768分辨率的整流图像显示为每秒60帧(FPS)的输出。实验结果表明整流图像具有几个垂直不匹配的像素。

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