High performance hardware architecture for depth measurement by using binocular-camera is proposed.In the system,at first,video streams of the target are captured by left and right charge-coupled device(CCD)cameras to...High performance hardware architecture for depth measurement by using binocular-camera is proposed.In the system,at first,video streams of the target are captured by left and right charge-coupled device(CCD)cameras to obtain an image including the target.Then,two different images with two different view points are obtained,and they are used in calculating the position deviation of the image's pixels based on triangular measurement.Finally,the three-dimensional coordinate of the object is reconstructed.All the video data is processed by using field-programmable gate array(FPGA)in real-time.Hardware implementation speeds up the performance and reduces the power,thus,this hardware architecture can be applied in the portable environment.展开更多
Typical single-pixel imaging techniques for edge detection are mostly based on first-order differential edge detection operators.In this paper,we present a novel edge detection scheme combining Fourier single-pixel im...Typical single-pixel imaging techniques for edge detection are mostly based on first-order differential edge detection operators.In this paper,we present a novel edge detection scheme combining Fourier single-pixel imaging with a second-order Laplacian of Gaussian(LoG)operator.This method utilizes the convolution results of an LoG operator and Fourier basis patterns as the modulated patterns to extract the edge detail of an unknown object without imaging it.The simulation and experimental results demonstrate that our scheme can ensure finer edge detail,especially under a noisy environment,and save half the processing time when compared with a traditional first-order Sobel operator.展开更多
文摘High performance hardware architecture for depth measurement by using binocular-camera is proposed.In the system,at first,video streams of the target are captured by left and right charge-coupled device(CCD)cameras to obtain an image including the target.Then,two different images with two different view points are obtained,and they are used in calculating the position deviation of the image's pixels based on triangular measurement.Finally,the three-dimensional coordinate of the object is reconstructed.All the video data is processed by using field-programmable gate array(FPGA)in real-time.Hardware implementation speeds up the performance and reduces the power,thus,this hardware architecture can be applied in the portable environment.
基金supported by the National Natural Science Foundation of China(Nos.61871431,61971184,and 62001162)China Postdoctoral Science Foundation(No.2019M662767)。
文摘Typical single-pixel imaging techniques for edge detection are mostly based on first-order differential edge detection operators.In this paper,we present a novel edge detection scheme combining Fourier single-pixel imaging with a second-order Laplacian of Gaussian(LoG)operator.This method utilizes the convolution results of an LoG operator and Fourier basis patterns as the modulated patterns to extract the edge detail of an unknown object without imaging it.The simulation and experimental results demonstrate that our scheme can ensure finer edge detail,especially under a noisy environment,and save half the processing time when compared with a traditional first-order Sobel operator.
