Localization of spherical fruits for robotic harvesting

The orange picking robot (OPR) is a project for developing a robot that is able to harvest oranges automatically. One of the key tasks in this robotic application is to identify the fruit and to measure its location in three dimensions. This should be performed using image processing techniques which must be sufficiently robust to cope with variations in lighting conditions and a changing environment. This paper describes the image processing system developed so far to guide automatic harvesting of oranges, which here has been integrated in the first complete full-scale prototype OPR. Received: 16 April 2000 / Accepted: 19 December 2000     

Real-time seam tracking for robotic laser welding using trajectory-based control

In this paper a real-time seam tracking algorithm is proposed that can cope with the accuracy demands of robotic laser welding. A trajectory-based control architecture is presented, which had to be developed for this seam tracking algorithm. Cartesian locations (position and orientation) are added to the robot trajectory during the robot motion. In this way, sensor information obtained during the robot motion is used to generate the robot trajectory while moving. Experiments have been performed to prove the tracking capabilities of the seam tracking algorithm.     

基于多光谱图像配准融合的机器人巡检平台

针对变电站中开展机器人巡检工作时,普遍存在复杂场景下拍摄所得红外与可见光检测图像存在遮挡、旋转和视角差异等情况,进而导致图像匹配融合效率低的问题,本文提出了一种基于STM32控制的多光谱图像配准融合巡检机器人模型。该模型首先建立模板库,通过模板匹配定位图像中的目标电力设备,在此基础上使用SURF算法进行精细匹配,即利用RANSAC剔除设备特征误配点,并采用单映射FINDHOMOGRAPHY算法进行像素叠加,最终实现变电站设备的红外、可见光图像融合。实验结果表明,本文的改进算法生成特征点数量合适、质量提升明显,相比SIFT、SURF等传统图像融合算法,配准精度提高至少30%,图像处理速度提高至少30%,具备实用意义,可有效应用于设备识别、电力设备故障诊断领域。     

基于图像序列拓扑关系的扎针机器人控制系统设计

由于当前扎针机器人定位参数存在误差,导致扎针成功率低,造成患者要忍受多次痛苦的问题,设计了一种扎针机器人控制系统。该系统由机械臂部分、上位机控制系统、高清激光图像采集系统、和信号传感器等部分组成,主要硬件部分选用DHT01型医用高清镜头、PCI8814图像采集卡、和性能更强的ATMEGA32L型单片机,保障采集图片的清晰度和对机械臂的控制精度。在图像序列处理算法上计算多帧图像的相似度,使用FAST算子提取图像的特征点,并基于关键帧优化图像序列的拓扑关系,实现目标位置的准确定位。实验结果表明,提出扎针机器人系统设计在3个轴向的偏差度平均值分别为0.0449、0.0383、和0.0387,趋近于理论上的中心位置,扎针一次成功率可以达到94.50%。     

一种基于GOR+GPU算法的机器人视觉导航方法

提出一种一般物体识别(GOR)方法.借鉴词袋(BOW)的统计模型,利用SIFT(尺度不变特征变换)检测算子进行特征向量描述.为了增加信息的冗余度,利用物体部件空间关系的统计信息来描述一幅图片中所有特征点的空间(相对距离和角度)关系,增广了原BOW模型中的特征向量.运用无监督判别分类器支持向量机(SVM)来实现分类识别.与此同时,采用GPU加速技术来实现SIFT特征提取与描述,以保证其实时性.然后,存手绘地图辅助导航的基础上,将该方法成功地应用到室内移动机器人导航上.实验结果表明,基于该方法的机器人导航技术具有较强的鲁棒性和有效性.     

基于DCT和DWT的彩色图像盲数字水印算法

提出了一种实用的基于离散余弦变换和离散小波变换的彩色图像盲数字水印算法.通过实验测试,提出的算法很好地保持了图像质量,对诸如JPEG压缩、滤波、噪声污染、缩放、剪切、马赛克效果、锐化等常见的信号处理和攻击均具有很强的鲁棒性.     

A genetic expectation-maximization method for unsupervised change detection in multitemporal SAR imagery

In this paper, we present a novel, automatic and unsupervised change-detection approach to the analysis of single-channel single-polarization multitemporal SAR images. The statistical parameters of the changed and unchanged classes, which are assumed to follow a generalized Gaussian (GG) distribution in the analysed log-ratio image, are explicitly estimated by the expectation-maximization (EM) algorithm initialized with a robust strategy based on genetic algorithms (GAs). In addition, the proposed approach integrates two further processing capabilities. The first one intends to cope with the problem of the automatic detection of multiple changes in the scene. This is carried out by modelling the log-ratio image histogram with a multimodal GG mixture whose number of components is estimated basing on the Bayesian information criterion (BIC). The second processing capability allows exploitation of spatial contextual information in the change detection process through a Markovian formulation. Results obtained on both simulated and real data are reported and discussed.     

Real time vision-based measurements for quality control of industrial rods on a moving conveyor

This work proposes a fully automated approach for vision-based quality control of manufactured metal rods. The proposed approach is able to detect the main axis of the rod and calculate its curvature, versus specifications. The proposed algorithm utilizes video acquired in real time by a single mono-ocular USB camera. A signal processing module identifies in real time the video frame that images the rod at the appropriate position on the conveyor. Initialization of the algorithm can take place either manually, or by utilizing the calibration of the camera. Concurrently, the image processing module estimates the curvature of the rod using its medial axis, to classify the rod as normal or defect. Initial results show that the proposed algorithm can operate in real time with very high accuracy under controlled illumination conditions and backgrounds. This methodology is capable of processing video at 30 frames per second, using a general purpose laptop.     

移动机器人基于三维激光测距的室内场景认知

研究了移动机器人在室内三维环境中的场景认知问题.室内场景框架具有结构化特性,而室 内多样化的物体则难以进行模型化表述. 本文利用区域扩张算法进行平面特征的提取,并根据平面属性及其相互间的空间关系,完成室 内场景框架的辨识.为了借鉴图像处理领域的物体识别方法, 本文提出一种基于Bearing Angle模型的激光测距数据表述方法,从而将三维点云数据转换为二维Bearing Angle图. 同一类物体中的个体形态具有多样性,同时观测视角也导致激光测距数据的显著差异.针对这些 问题,采用一种基于Gentleboost算法的有监督学习方法, 并利用物体碎片及其相对于物体中心的位置作为特征,从而完成室内场景中的物体认知. 利用室内场景框架辨识结果在Bearing Angle图中进行天棚、地面、墙壁、房门等区域的标记,并利用所产生的语义信息去除错误的认知结果,从而有助于提高识别率. 利用实际机器人平台所获得的实验结果验证了所提方法的有效性.     

基于DWT的图像水印算法研究

提出了一种基于离散小波变换的水印算法。水印采用文本图像水印,将原始图像和水印分别进行3级小波变换,为了保证水印的安全性,将水印变换域各子图分别进行置乱或加密处理。将水印经处理后的各级变换系数重复嵌入原始图像各级变换系数的不同位置。在检测时,提出采用多方案水印提取算法以适应不同的攻击。实验表明对缩放、剪切、JPEG或JPEG2000压缩等图像退化处理或攻击均具有较强的鲁棒性。     

边缘检测技术在工件中心位置识别中的应用

图像的边缘检测技术是图像处理的重要内容,利用边缘检测结果对图像进行分析,找出图像中工件的中心位置往往是实际工作中的主要内容。在边缘检测中,利用改进的LOG算法结果,对有矩形、有圆的工件图像进行了中心识别,并给出了各种算法与实际中心坐标的误差对比,为机器人抓取工件及其他作业中的定位奠定了理论基础。     

一种基于小波变换的自适应图像水印算法

在离散小波变换的基础上，提出了一种自适应的新数字水印算法，将伪随机二值序列作为水印嵌入灰度图像中，在检测端需要原始宿主图像。该算法具有以下特点：在水印嵌入时利用了小波变换域系数的均值，可广泛地适用于各种灰度图像；针对每幅图像，都可调节水印的嵌入深度，找到隐形性和鲁棒性的最佳折中。实验结果表明，该算法既实现了水印的隐形性，又对常见的图像处理操作具有很强的鲁棒性。     

Autonomous Acquisition of Seam Coordinates for Arc Welding Robot Based on Visual Servoing

Autonomous acquisition of seam coordinates is a key technology for developing advanced welding robot. This paper describes a position-based visual servo system for robotic seam tracking, which is able to autonomously acquire the seam coordinates of the planar butt joint in the robot base frame and plan the optimal camera angle before welding. A six-axis industrial robot is used in this system, which has an interface for communicating with the master computer. The developed visual sensor device is briefly presented that allows the charge-coupled device (CCD) cameras to rotate about the torch. A set of robust image processing algorithms are proposed so that no special requirements of light source are needed in this system. The feedback errors of this servo system are defined according to the characteristics of the seam image, and the robust tracking controller is developed. Both the image processing program and tracking control program run on the master computer. The experimental results on straight line seam and curve seam show that the accuracy of the seam coordinates acquired with this method is more adequate for high quality welding process.     

A Robust Docking Strategy for a Mobile Robot Using Flow Field Divergence

We present a robust strategy for docking a mobile robot in close proximity with an upright surface using optical flow field divergence and proportional feedback control. Unlike previous approaches, we achieve this without the need for explicit segmentation of features in the image, and using complete gradient-based optical flow estimation (i.e., no affine models) in the optical flow computation. A key contribution is the development of an algorithm to compute the flow field divergence, or time-to-contact, in a manner that is robust to small rotations of the robot during ego-motion. This is done by tracking the focus of expansion of the flow field and using this to compensate for ego rotation of the image. The control law used is a simple proportional feedback, using the unfiltered flow field divergence as an input, for a dynamic vehicle model. Closed-loop stability analysis of docking under the proposed feedback is provided. Performance of the flow field divergence algorithm is demonstrated using offboard natural image sequences, and the performance of the closed-loop system is experimentally demonstrated by control of a mobile robot approaching a wall.      

一种基于DCT和SVD的数字图像水印技术

以离散余弦变换(DCT)、矩阵奇异值分解(SVD)为基础,提出一种数字水印算法,主要特点就是所嵌入的水印图像是灰度图像,增加了嵌入的信息量,能够满足数字水印系统的透明性和鲁棒性要求。实验结果表明:该算法不仅具有较好的透明性,而且对如叠加噪声、JPEG压缩、中值滤波、低通滤波、对比度增强攻击均具有很好的鲁棒性。     

基于光幕触发CCD交汇连发弹丸坐标处理方法研究

针对CCD线阵交汇系统中测试弹丸连发坐标时以最大帧频连续拍摄,数据量过大而导致处理时间过长的问题,提出一种基于基于激光光幕触发的多峰值检测和自适应阈值弹丸检测的快速检测连发弹丸坐标方法。采用90°的“一”字线型半导体激光器配合原向反射屏形成光电探测靶面,光电转换模块将弹丸过靶时引起的光通量变化转换成电信号产生过靶信号,处理数据时先使用多峰值检测算法,根据获得的过靶信号波形计算出所有弹丸的过靶时刻和对应图像位置信息,并将该幅图像和临近两幅图像拼接成一幅组合图像作为该发弹丸的过靶图像,再使用基于自适应阈值的弹丸检测算法对其进行弹丸目标检测得到弹丸坐标。当该图像检测出多个像素坐标时,使用像素坐标剔除算法进行处理得到准确坐标。最后进行了4组对照试验,在得到正确连发坐标的前提下分别统计本文方法与传统方法的处理时间。结果表明与处理所有图像的传统方法相比,本文提出的方法在保证连发弹丸坐标正确率的前提下,提高了处理速度。     

Virtual sensors for human concepts—Building detection by an outdoor mobile robot

In human–robot communication it is often important to relate robot sensor readings to concepts used by humans. We suggest the use of a virtual sensor (one or several physical sensors with a dedicated signal processing unit for the recognition of real world concepts) and a method with which the virtual sensor can learn from a set of generic features. The virtual sensor robustly establishes the link between sensor data and a particular human concept. In this work, we present a virtual sensor for building detection that uses vision and machine learning to classify the image content in a particular direction as representing buildings or non-buildings. The virtual sensor is trained on a diverse set of image data, using features extracted from grey level images. The features are based on edge orientation, the configurations of these edges, and on grey level clustering. To combine these features, the AdaBoost algorithm is applied. Our experiments with an outdoor mobile robot show that the method is able to separate buildings from nature with a high classification rate, and to extrapolate well to images collected under different conditions. Finally, the virtual sensor is applied on the mobile robot, combining its classifications of sub-images from a panoramic view with spatial information (in the form of location and orientation of the robot) in order to communicate the likely locations of buildings to a remote human operator.     

机器人足球视觉系统中的实时图像处理

视觉系统是整个机器人足球系统的重要组成部分。根据机器人足球视觉系统的特点,提出基于游程长度编码(RLE)的实时快速图像处理算法。算法使用RLE对图像进行压缩,并且在处理阶段高效识别出图像中目标的尺寸和位置。压缩阶段算法的时间复杂度与图像尺寸成线性关系,图像处理阶段算法的时间复杂度与图像中目标的个数和每个目标所占的扫描行数成线性关系。     

Wavelet-based image registration technique for high-resolution remote sensing images

Image registration is the process of geometrically aligning one image to another image of the same scene taken from different viewpoints at different times or by different sensors. It is an important image processing procedure in remote sensing and has been studied by remote sensing image processing professionals for several decades. Nevertheless, it is still difficult to find an accurate, robust, and automatic image registration method, and most existing image registration methods are designed for a particular application. High-resolution remote sensing images have made it more convenient for professionals to study the Earth; however, they also create new challenges when traditional processing methods are used. In terms of image registration, a number of problems exist in the registration of high-resolution images: (1) the increased relief displacements, introduced by increasing the spatial resolution and lowering the altitude of the sensors, cause obvious geometric distortion in local areas where elevation variation exists; (2) precisely locating control points in high-resolution images is not as simple as in moderate-resolution images; (3) a large number of control points are required for a precise registration, which is a tedious and time-consuming process; and (4) high data volume often affects the processing speed in the image registration. Thus, the demand for an image registration approach that can reduce the above problems is growing. This study proposes a new image registration technique, which is based on the combination of feature-based matching (FBM) and area-based matching (ABM). A wavelet-based feature extraction technique and a normalized cross-correlation matching and relaxation-based image matching techniques are employed in this new method. Two pairs of data sets, one pair of IKONOS panchromatic images from different times and the other pair of images consisting of an IKONOS panchromatic image and a QuickBird multispectral image, are used to evaluate the proposed image registration algorithm. The experimental results show that the proposed algorithm can select sufficient control points semi-automatically to reduce the local distortions caused by local height variation, resulting in improved image registration results.