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Intelligent Robots and Computer Vision xiv: algorithms, Techniques, Active Vision, and Materials Handling

ISBN: (纸本)0819419524

This conference proceedings contain 70 papers. Topics covered include:Pattern recognition in intelligent robotics;Active vision and control;Color image processing;systems and applications;Robotic navigation, path planning, and use of motion and image sequences;3D modeling and data processing for robotics and machine vision;Three dimensional pattern recognition for intelligent robots;Neural nets for pattern recognition and machine vision;Feature extraction;and;Detection and segmentation in machine vision.

关键词： Computer vision

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Novel approach to visual robot control

Novel approach to visual robot control

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Conference on Intelligent Robots and Computer Vision xiv - algorithms, Techniques, Active Vision, and Materials Handling

作者： Prljaca, N McCabe, H Dublin City Univ SCH ELECTR ENGN DUBLIN IRELAND

ISBN: (纸本)0819419524

In this paper a new control scheme for a robot manipulator based on visual information is proposed. The control system determines the position and orientation of the robot gripper in order to achieve desired grasping relation between the gripper and a 3D object. The proposed control scheme consists of two distinct stages: (1) Learning stage, in this stage the robot system reconstructs a 3D geometrical model of a presented unknown object within a class of objects (polyhedra), by integrating information from an image sequence obtained from a camera mounted on the robot manipulator (eye-in-hand). This model is represented by a set of 3D line segments and denoted as a reference model. The robot is also taught desired grasping relation by manual guidance. (2) Execution stage, in this stage the robot system reconstructs a 3D model of the arbitrarily placed 3D object. This model is denoted as an observed model. Then, the necessary position and orientation of its gripper is determined based on estimated 3D displacement between the reference and observed models. Further, the basic algorithm is extended to handle multiple objects manipulation and recognition. The performance of the proposed algorithms has been tested on the real robot system and the experimental results are presented.

关键词： 3D modeling 3D metrology 3D image processing Detection and tracking algorithms Motion models Visualization Eye models Cameras Robotic systems Control systems

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3D model matching for fine pose determination

3D model matching for fine pose determination

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Intelligent Robots and Computer Vision xiv: algorithms, Techniques, Active Vision, and Materials Handling

作者： Peurach, Thomas Whalen, Margaret J. Haanpaa, Douglas Cybernet Systems Corp. Ann Arbor MI USA

ISBN: (纸本)0819419524

3D model matching is the process of matching image features to 3D model features. The feature correspondences are used to determine the transformation between the model and camera and thus, define the orientation of the object. The solution to this 3D model matching is difficult to calculate due to the high dimensionality of the solution space. Addressing this problem, we have developed a machine-vision system which incorporates an advanced iterative search procedure and Hough transform feature extraction into a system which avoids image segmentation to determine the fine pose of some objects. Inputs to the system include images of the object from various camera views, a coarse pose estimate and a CAD object model. A windowing grid system is applied to the scene image(s) and a single feature hypothesis is extracted from each window. A modified Newton-Raphson iterative search method is used to evaluate mappings between the image features and model features. The search attempts to optimize a cost function which is based on the perpendicular distance between linear features. Results have shown that the described fine pose determination method can achieve sub pixel accuracy when applied to images of various geometric shapes. The system has been applied to a number of applications including space rendezvous and docking, ordnance defusing, and missile tracking.

关键词： image processing

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The development of an autonomous space robot operation testbed: ASROT2/25/2016

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Advanced Robotics 1993年第1期8卷 45-59页

作者： Komatsuss, Tadashi Uenohara, Michihiro Iikura, Shoichi Miura, Hirofumi Shimoyama, Isao Mechanical Engineering Lab. R&D Center Toshiba Corp. 4-1 Ukishima-cho Kawasaki-ku Kawasaki 210 Japan Research and Development Center Toshiba Corp. Kawasaki 210 Japan Research and Development Center Toshiba Corp. Kawasaki 210 Japan Faculty of Engineering The University of Tokyo Bunkyo-ku Tokyo 113 Japan Faculty of Engineering The University of Tokyo Bunkyo-ku Tokyo 113 Japan

We have developed a two-dimensional operation testbed for an autonomous free-flying space robot such as an orbital manoeuvring vehicle. This system has been named ASROT (autonomous space robot operation testbed). Basically, ASROT consists of a satellite robot, a target, a host computer, and a planar base. The host computer is used only for observation and data gathering of the system. The satellite robot is a satellite which can accomplish various tasks with a manipulator. The satellite is 620 mm (W) x 805 mm (H) x 620 mm (L), and weighs 120 kg. This system floats on a planar base using air pads, and is able to fly around using thrusters for position control and a control moment gyro for attitude control. The manipulator is a 1.4 m long flexible arm. This paper proposes an operating system needed for real-time autonomous control. The satellite robot contains hardware systems such as vision systems, board computers, and image processing units, and software systems such as algorithms for path planning. © 1993, VSP. All rights reserved.

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INTEGRATED image-processing AND TRACKER PERFORMANCE PREDICTION WORKSTATION 14

INTEGRATED IMAGE-PROCESSING AND TRACKER PERFORMANCE PREDICTI...

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CONF ON APPLICATIONS OF DIGITAL image processing 14

作者： SCHNEEBERGER, TJ MCINTIRE, HD Applied Technology Associates Inc. (United States)

ISBN: (纸本)0819406953

Extensive research has shown that including target aspect angle measurements from an optical sensor can significantly improve the performance of radar tracking systems. Integrating sequences of target imagery with the kinematic information involves sets of image processing and sensor data fusion algorithms. A workstation has been developed to expedite the analysis of the algorithms and to integrate the image processing with selectable extended-state tracker modules. This workstation can access analog video imagery from a video optical disk controlled by a PC, segment the target in the image, and perform target identification and aspect angle estimation using a database of target models which span the range of possible aspects. The angle information is then `fused' with kinematic data to augment the tracker state estimator. The workstation is implemented with a powerful visual user interface in a UNIX/X- Windows environment, and includes a wide array of image and signal processing algorithms. Interactive modifications of processing sequences and `what if' analyses are easily conducted. The workstation provides a consistent user interface across a variety of applications. This system has also been used to implement phase retrieval and related image recovery algorithms.

关键词： image segmentation image processing Detection and tracking algorithms Human-machine interfaces Algorithm development Digital image processing Radar Visualization image fusion image processing algorithms and systems

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NONLINEAR OPTICAL-FLOW ESTIMATION AND SEGMENTATION 14

NONLINEAR OPTICAL-FLOW ESTIMATION AND SEGMENTATION

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CONF ON APPLICATIONS OF DIGITAL image processing 14

作者： GEURTZ, AM Ecole Polytechnique Federale de Lausanne (Switzerland)

ISBN: (纸本)0819406953

We present an algorithm for the joint estimation and segmentation of optical flow from gradient data, based on considerations from image grey level segmentation. Some first simulation results are shown and compared to existing spatial domain flow estimation algorithms. Promising results as well as strong indications for future enhancements are obtained.

关键词： image segmentation Optical flow Digital image processing image processing algorithms and systems Distance measurement Computer vision technology Data modeling Machine vision Motion estimation Motion models

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TOROS - AN image-processing SYSTEM FOR MEASURING CONSIGNMENTS OF WOOD 14

TOROS - AN IMAGE-PROCESSING SYSTEM FOR MEASURING CONSIGNMENT...

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CONF ON APPLICATIONS OF DIGITAL image processing 14

作者： CORREIA, B DAVIES, R CARVALHO, F RODRIGUES, FC LNETI-OPTICA (Portugal)

ISBN: (纸本)0819406953

Traditionally, the quantity of wood in a truckload of logs is evaluated by a manual measurement of the enclosing volume. This paper describes the method developed at LNETI for measuring automatically the volume of a consignment of logs. The PC-based central unit processes the images from several solid-state medium-resolution cameras, using the software developed. The computer vision system, the image processing algorithms implemented therein, and the results obtained are presented.

关键词： image processing Digital image processing Cameras image segmentation Computing systems Solids Calibration Algorithm development image resolution Software development

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UNSUPERVISED TARGET DETECTION IN A SINGLE IR image FRAME 14

UNSUPERVISED TARGET DETECTION IN A SINGLE IR IMAGE FRAME

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CONF ON APPLICATIONS OF DIGITAL image processing 14

作者： ZHOU, YT HNC Inc. (United States)

ISBN: (纸本)0819406953

Detecting targets from infrared (IR) images in the absence of a priori information is a very difficult task. In this paper, we present an unsupervised detection algorithm based on Gabor functions for detecting targets from a single IR image frame. The only explicit assumption made is that the targets can be considered a rectangle. The algorithm consists of three steps. First, it locates potential targets based on a rectangle matching pattern by using low resolution Gabor functions which resist noise and background clutter effects. Then it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low and high resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles and aircraft with different size and brightness in various background scenes and orientations.

关键词： Target detection Detection and tracking algorithms Evolutionary algorithms Infrared imaging Digital image processing Algorithm development image processing algorithms and systems Infrared detectors Human vision and color perception image segmentation

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HST PHASE RETRIEVAL - A PARAMETER-ESTIMATION 14

HST PHASE RETRIEVAL - A PARAMETER-ESTIMATION

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CONF ON APPLICATIONS OF DIGITAL image processing 14

作者： LYON, RG MILLER, PE GRUSCZAK, A Hughes Danbury Optical Systems (United States)

ISBN: (纸本)0819406953

It was found, on orbit, that the Hubble Space Telescope had a conic constant error in the primary mirror. The result of the error is a substantial amount of spherical aberration in the image, significantly reducing image resolution and encircled energy. Parametric phase retrieval was the method used to determine the source of error and to find the magnitude from on-board camera images. The parameters which are estimated are a set of annular Zernike polynomials which are analogous to the classical aberrations. This was one of the first practical uses of phase retrieval for on-orbit measurement. This paper contains an overview of the algorithms, how they were used and the major results.

关键词： Point spread functions Phase retrieval Cameras Mirrors Monochromatic aberrations Optical fiber cables Digital image processing Zernike polynomials Objectives Relays

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EXTRACTING FEATURES TO RECOGNIZE PARTIALLY OCCLUDED OBJECTS 14

EXTRACTING FEATURES TO RECOGNIZE PARTIALLY OCCLUDED OBJECTS

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CONF ON APPLICATIONS OF DIGITAL image processing 14

作者： KOCH, MW RAMAMURTHY, A Clarkson Univ. (United States) Electro-Optical Information Systems (United States)

ISBN: (纸本)0819406953

Noisy objects, partially occluded objects, and objects in random positions and orientations cause significant problems for current robotic vision systems. In the past, an association graph has formed the basis for many model based matching methods. However, the association graph has many false nodes due to local and noisy features. Objects having similar local structures create many false arcs in the association graph. The maximal clique recursive and tree search procedures for finding sets of structurally compatible matches have exponential time complexity, due to these false arcs and nodes. This represents a real problem as the number of objects appearing in the scene and the model set size increase. Our approach is similar to randomized string matching algorithms. Points on edges represent the model features. A fingerprint defines a subset of model features that uniquely identify the model. These fingerprints remove the ambiguities and inconsistencies present in the association graph and eliminate the problems of Turney's connected salient features. The vision system chooses the fingerprints at random, preventing a knowledgeable adversary from constructing examples that destroy the advantages of fingerprinting. Fingerprints consist of local model features called point vectors. We have developed a heuristic approach for extracting fingerprints from a set of model objects. A list of connected and unconnected scene edges represent the scene. A Hough transform type approach matches model fingerprints to scene features. Results are given for scenes containing varying amounts of occlusion.

关键词： Visual process modeling Detection and tracking algorithms image segmentation Digital image processing Electro optical modeling Feature extraction Hough transforms Stars Quantization systems modeling

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