New Gabor transform (GT) filters to detect candidate object locations independent of the object class, object distortions, and for low contrast objects in clutter are described. A new neural network (NN) technique is ...
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ISBN:
(纸本)0819413208
New Gabor transform (GT) filters to detect candidate object locations independent of the object class, object distortions, and for low contrast objects in clutter are described. A new neural network (NN) technique is described to automate selection of GT parameters and to combine multiple Gabor functions (GFs) into once composite macro GF detection filter. Fusion of real and imaginary GT filter outputs is used to reduce false alarms, (PFA), while maintaining high detection rates (PD). Test results on the TRIM-2 database are provided.
Autonomous and guide assisted vehicles make a heavy use of computervisiontechniques to perceive the environment where they move. In this context, the European PROMETHEUS program is carrying on activities in order to...
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ISBN:
(纸本)0819413208
Autonomous and guide assisted vehicles make a heavy use of computervisiontechniques to perceive the environment where they move. In this context, the European PROMETHEUS program is carrying on activities in order to develop autonomous vehicle monitoring that assists people to achieve safer driving. Car detection is one of the topics that are faced by the program. Our contribution proposes the development of this task in two stages: the localization of areas of interest and the formulation of object hypotheses. In particular, the present paper proposes a new approach that builds structural descriptions of objects from edge segmentations by using geometrical organization. This approach has been applied to the detection of cars in traffic scenes. We have analyzed images taken from a moving vehicle in order to formulate obstacle hypotheses: preliminary results confirm the efficiency of the method.
Fov improving underwater visibility for robots. a method using special intervallic series of light pulses, and two acts of emitting and receiving are performed by two special designed optical shutters and the control ...
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In this paper, a high-resolution algorithm for detecting the orientation and position of an IC, and an algorithm for compensating the position and skew angle of a PCB, are proposed. The proposed algorithm for the firs...
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ISBN:
(纸本)0819413208
In this paper, a high-resolution algorithm for detecting the orientation and position of an IC, and an algorithm for compensating the position and skew angle of a PCB, are proposed. The proposed algorithm for the first topic consists of two parts. Its first part is a preprocessing step, in which corner points of an IC are detected and are separated into two groups. Then the coarse angle of the principal axis is obtained by line fitting. The second part is a main processing step, in which the Hough transform over the limited range of angles is applied to the corner points to detect precisely the orientation of an IC or a surface mounting device (SMD). The position of an IC or SMD is determined by using its four corner points. The proposed algorithm for the second topic is the one which detects a rotation angle and translation parameters of a PCB using a template matching method. The PCB is compensated by the detected parameters. The computer simulation shows that the parameters obtained by proposed algorithms are more accurate than those by the several conventional methods considered. The proposed algorithms can be applied to the fast and accurate automatic inspection systems.
We discuss recent results from our ongoing research concerning the application of artificial evolution techniques (i.e., an extended form of genetic algorithm) to the problem of developing `neural' network control...
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ISBN:
(纸本)0819413208
We discuss recent results from our ongoing research concerning the application of artificial evolution techniques (i.e., an extended form of genetic algorithm) to the problem of developing `neural' network controllers for visually guided robots. The robot is a small autonomous vehicle with extremely low-resolution vision, employing visual sensors which could readily be constructed from discrete analog components. In addition to visual sensing, the robot is equipped with a small number of mechanical tactile sensors. Activity from the sensors is fed to a recurrent dynamical artificial `neural' network, which acts as the robot controller, providing signals to motors governing the robot's motion. Prior to presentation of new results, this paper summarizes our rationale and past work, which has demonstrated that visually guided control networks can arise without any explicit specification that visual processing should be employed: the evolutionary process opportunistically makes use of visual information if it is available.
Scenes of polyhedral objects may be accurately represented in 2-D using line sketches. An aim of low level image processing is to generate useful binary images from grey scale images. The binary images generated by en...
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ISBN:
(纸本)0819413208
Scenes of polyhedral objects may be accurately represented in 2-D using line sketches. An aim of low level image processing is to generate useful binary images from grey scale images. The binary images generated by enhancement/threshold edge detectors are usually unrefined outlines of the underlying 3-D scene. Such images must be further processed to isolate and identify region boundaries; which, in the case of polyhedra, consist of line segments. The intersection or connection points of these line segments are known as vertices or corners. The work reported in this paper employs a decision theoretic approach to detect vertices in grey scale images.
Shape classification via linear granulometric moments is examined for patterns suffering varying degrees of edge noise. It is seen that recognition is quite poor even for modest amounts of noise and remains poor even ...
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ISBN:
(纸本)0819413208
Shape classification via linear granulometric moments is examined for patterns suffering varying degrees of edge noise. It is seen that recognition is quite poor even for modest amounts of noise and remains poor even when the patterns are first filtered by a close-open filter. Recognition accuracy is greatly improved, for both unfiltered and filtered images, by employing exterior granulometries. These are constructed by applying the various linear structuring-element sequences to the corresponding linear convex hulls of the noisy patterns. The resulting granulometric distributions are then not corrupted by noise-induced probability mass at the left of the pattern spectrum, thereby greatly diminishing the detrimental effects on the pattern spectrum moments.
The conference materials contain 71 papers. The main topics covered include pattern recognition in computervision;locating edges, lines curves, and surfaces in robotic vision;segmentation, motion, and color technique...
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ISBN:
(纸本)0819410268
The conference materials contain 71 papers. The main topics covered include pattern recognition in computervision;locating edges, lines curves, and surfaces in robotic vision;segmentation, motion, and color techniques;morphological processing for intelligent robotics;sensory robotics and control: vision, collision avoidance, path planning;visual servoing in automated manufacturing;and active vision.
The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active ...
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ISBN:
(纸本)0819413208
The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active vision system architecture that is based loosely upon the parallel-hierarchical (pyramidal) structure of the biological visual pathway is presented in this paper. Although the computational architecture of the proposed pyramidal neuro-vision system is far less sophisticated than the architecture of the biological visual pathway, it does retain some essential features such as the converging multilayered structure of its biological counterpart. In terms of visual information processing, the neuro-vision system is constructed from a hierarchy of several interactive computational levels, whereupon each level contains one or more nonlinear parallel processors. Computationally efficient vision machines can be developed by utilizing both the parallel and serial information processing techniques within the pyramidal computing architecture. A computer simulation of a pyramidal vision system for active scene surveillance is presented.
By virtue of their functional approximation, learning and adaptive capabilities, the computational neural networks can be suitably employed for learning robot coordinate transformations. The major drawback of conventi...
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ISBN:
(纸本)0819413208
By virtue of their functional approximation, learning and adaptive capabilities, the computational neural networks can be suitably employed for learning robot coordinate transformations. The major drawback of conventional static feedforward neural networks based on back-propagation learning algorithm is in their very large convergence time for a given task. Any attempts to accelerate the learning process by increasing the values of learning constants in the algorithm often result in unstable systems. The intent of this paper is to describe a neural network structure called dynamic neural processor (DNP), and examine briefly how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. computer simulations are provided to demonstrate the effectiveness of the proposed learning scheme using the DNP.
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