基于改进BP神经网络的移动机器人寻线控制

神经网络系统具有自学习和自适应的能力,同时有很强的容错性和鲁棒性,适用于处理难于语言化的模式信息。为使移动机器人沿地面标志线自主运动,采用CCD图像传感器与PC／104总线相结合的硬件系统,运用神经网络的模式识别功能,实现了机器人的寻线控制,实验结果表明该方法是可行的,能有效地提高移动机器人对环境的适应性和其智能化水平。     

基于CCD的垂线坐标仪的设计

针对矿井井壁变形引起的径向位移测量问题,提出了一种基于CCD的垂线坐标仪的设计方案,给出了垂线坐标仪的结构及其在井壁变形监测系统中的布置,详细介绍了垂线坐标仪的软、硬件设计。该垂线坐标仪利用CCD采集光信号并将其转换为视频信号,采用LPC932对采集的视频信号进行二值化处理及计数,并将处理结果发送至地面计算机进行分析,从而得到矿井井壁变形引起的径向位移量。测试结果验证了该垂线坐标仪的稳定性和精确性。     

综放采煤自动化煤岩识别传感器的研究

在实现综放采煤自动化的过程中,能准确检测区分出煤和岩石是实现无人作业工作面的难点.在高速数字信号处理器(DSP)平台上建立CCD数字处理系统,通过DSP对图像的离散脉冲噪声进行中值滤波,并实时计算出每一张图像的灰度直方图,提取煤炭和岩石的特征区别,从而实现对综放工作面的控制.通过Matlab仿真和实际测试结果表明:检测...     

Shape Reconstruction and Camera Self-Calibration Using Cast Shadows and Scene Geometries

Recently, various techniques of shape reconstruction using cast shadows have been proposed. These techniques have the advantage that they can be applied to various scenes, including outdoor scenes, without using special devices. Previously proposed techniques usually require calibration of camera parameters and light source positions, and such calibration processes limit the range of application of these techniques. In this paper, we propose a method to reconstruct 3D scenes even when the camera parameters or light source positions are unknown. The technique first recovers the shape with 4-DOF indeterminacy using coplanarities obtained by cast shadows of straight edges or visible planes in a scene, and then upgrades the shape using metric constraints obtained from the geometrical constraints in the scene. In order to circumvent the need for calibrations and special devices, we propose both linear and nonlinear methods in this paper. Experiments using simulated and real images verified the effectiveness of this technique.     

基于CCD的掌纹掌脉采集模块设计

针对掌纹掌脉身份认证的需求,以掌纹和掌静脉图像采集系统作为研究对象,设计了一种基于CCD的掌纹掌脉采集模块.采集模块采用单CCD作为图像感应芯片,在单颗芯片上同时获得掌纹掌脉图像,光源设计上突破性地采用了激光二极管作为红外补充光源,采集的图像以USB数据形式进行上传.实验表明:采集模块能够获得满足图像处理要求的清晰可靠的掌纹掌脉图像.     

近景大视场角分区域标定方法研究

针对飞行试验测量视场大相机标定精度低的问题,提出一种高精度CCD相机分区域标定方法。该方法首先通过将标靶均匀布置在摄像机视场内,使得标靶尽可能均匀错落地充满整个视场范围,再结合人眼判读的方式求解靶标的像面位置,最终与全站仪三维坐标形成精确的空间标定点集。接着,将像平面按横向方向等间距分割成Ｎ个区域,并结合后方交会的方法分别对每个子区域进行相机参数的计算。实验结果表明：经过分区域标定,相机采集点的总误差比单区域标定法降低了4％(Ｎ＝3)。算法可实现指定区域的相机参数计算,基本满足中高等精度的工业测量要求。所本文研究可应用于位置相对固定不变的工业视觉测量,特别是大工件测量领域。     

Multi-camera calibration based on an invariant pattern

In this paper we present a method for the calibration of multiple cameras based on the extraction and use of the physical characteristics of a one-dimensional invariant pattern which is defined by four collinear markers. The advantages of this kind of pattern stand out in two key steps of the calibration process. In the initial step of camera calibration methods, related to sample points capture, the proposed method takes advantage of using a new technique for the capture and recognition of a robust sample of projective invariant patterns, which allows to capture simultaneously more than one invariant pattern in the tracking area and recognize each pattern individually as well as each marker that composes them. This process is executed in real time while capturing our sample of calibration points in the cameras of our system. This new feature allows to capture a more numerous and robust set of sample points than other patterns used for multi-camera calibration methods. In the last step of the calibration process, related to camera parameters' optimization, we explore the collinearity feature of the invariant pattern and add this feature in the camera parameters optimization model. This approach obtains better results in the computation of camera parameters. We present the results obtained with the calibration of two multi-camera systems using the proposed method and compare them with other methods from the literature.     

Robust refinement methods for camera calibration and 3D reconstruction from multiple images

This paper proposes robust refinement methods to improve the popular patch multi-view 3D reconstruction algorithm by Furukawa and Ponce (2008). Specifically, a new method is proposed to improve the robustness by removing outliers based on a filtering approach. In addition, this work also proposes a method to divide the 3D points in to several buckets for applying the sparse bundle adjustment algorithm (SBA) individually, removing the outliers and finally merging them. The residuals are used to filter potential outliers to reduce the re-projection error used as the performance evaluation of refinement. In our experiments, the original mean re-projection error is about 47.6. After applying the proposed methods, the mean error is reduced to 2.13.     

基于FPGA的CCD相机的图像采集

介绍在特定环境下CCD相机图像数据的采集背景下的一种基于FPGA的高速图像数据采集板卡设计方法,详细讨论了其系统结构和核心部分的内部功能模块,并给出了其核心：PCI IPcore的具体仿真结果。同时探讨了此板卡和外部的接口实现问题。     

基于FPGA的CCD相机的图像采集

介绍在特定环境下CCD相机图像数据的采集背景下的一种基于FPGA的高速图像数据采集板卡设计方法,详细讨论了其系统结构和核心部分的内部功能模块,并给出了其核心:PCI IPcore的具体仿真结果。同时探讨了此板卡和外部的接口实现问题。