After the stage of pointlike target tracking, the tracker comes to the stage of area target tracking. This paper considers the situation in which the FLIR image contains a number of targets. The targets are compact. T...
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ISBN:
(纸本)0819405914
After the stage of pointlike target tracking, the tracker comes to the stage of area target tracking. This paper considers the situation in which the FLIR image contains a number of targets. The targets are compact. The image segmentation is achieved by considering not only the global gray-level distribution but also the spatial distribution of target pixels. After the global gray-level statistics in the whole image, a recursive merging algorithm, a hierarchical clustering on the gray level and spatial position, is applied to segment the image into a multiple gray-level image. To make full use of the whole scene scan, a four direction code method is used to depict the edges of target regions. And to save more execution time, the useful features, including structure feature and geometry feature, are calculated by the four direction code expression at the same time. Thus the target edge description and the useful features calculation are finished in the same whole scene scan of the segmented image. A changing index table which describes targets and their features within the segmented image is set up. The index table is updated at each scene to depict the changing content of the image. During the time in which the image gets into a comparable stable state, a target recognition procedure may be applied to find the interested target, and the threatening value of each target is considered. An adaptive gate is assigned to each interested target.
Although facsimile systems have existed for more than twenty five years, only recently have we seen explosive growth in the use of facsimile, with a corresponding increase in facsimile standards activity. Current stan...
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A system assembled to study several aspects of locating ship targets from infrared imagery is described. The system was either placed on shore sites or installed on an aircraft to collect data on the scene. The primar...
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A system assembled to study several aspects of locating ship targets from infrared imagery is described. The system was either placed on shore sites or installed on an aircraft to collect data on the scene. The primary sensor was an infrared camera which produced images of the scene at standard RS-170 rates. Requirements that included real time operation dictated the use of a parallel architecture for this task. As no suitable commercial systems were available, a custom array of bit slice microprocessors was assembled for the task. Through extensive field tests strengths and limitations of the design have been identified. These lessons are being applied to the development of next generation systems. A gimbal mounted infrared camera with digitization circuitry presents a new 256 by 256 pixel image to the parallel pipelined array of 17 bit slice microprocessors thirty times a second. To extend processor performance beyond the standard commercial microprocessors, two basic bit slice designs were employed. The bit slice machines were highly tuned for the assigned tasks and algorithms. Unfortunately this restricted the desired flexibility to readily examine alternate algorithms. The fundamental architecture concept performed well quickly reducing the large array of data to manageable set of information. Real time operator displays were driven to monitor the progress of each test run.
The reconstruction of curves and surfaces from sparse data is an important task in many applications. In computer vision problems the reconstructed curves and surfaces generally represent some physical property of a r...
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The reconstruction of curves and surfaces from sparse data is an important task in many applications. In computer vision problems the reconstructed curves and surfaces generally represent some physical property of a real object in a scene. Thus, the characteristics of the reconstruction process differs from straight forward fitting of smooth curves and surfaces to a set of data. Since the collected data is represented in an arbitrarily chosen coordinate system, the reconstruction process should be invariant to the choice of the coordinate system (except for the transformation between the two coordinate systems). In this paper, reconstruction algorithms are presented for reconstructing invariant estimates of both curves and surfaces. The reconstruction problem will be cast as an ill-posed inverse problem which must be stablized using a priori information about the constraint formation. Tikhonov regularization is used to form a well-posed mathematical problem statement. Examples of typical reconstructed objects are also given.
optical flow-field obtained by the analysis of a sequential scene derived by a relative motion between object and camera includes three-dimensional information (depth and/or shape). This paper develops a spatio-tempor...
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optical flow-field obtained by the analysis of a sequential scene derived by a relative motion between object and camera includes three-dimensional information (depth and/or shape). This paper develops a spatio-temporal correlation method for determining optical flow and attempts to extract the depth information on the basis of the analyzed optical flow field and the principle of the 'motion stereo.' The method herein is improved in two critical points: (1) analysis of the plane wave propagation;and (2) algorithms for rapid calculation. It is demonstrated that the improved method and the theory of 'motion stereo' are available for extracting depth information from actual scenes.
Various approaches have been proposed toward the problem of restoring three-dimensional (3-D) structures and motion of rigid bodies from image information. Ullman and Huang presented algorithms using point and line co...
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Various approaches have been proposed toward the problem of restoring three-dimensional (3-D) structures and motion of rigid bodies from image information. Ullman and Huang presented algorithms using point and line correspondences, in which they assume that the correspondence problems can be solved. Prazdny et al., on the other hand, presented an algorithm using optical flow, in which equations becomes nonlinear and thus the second derivative of velocity is required. This paper proposes an algorithm which combines optical flow and edge information. First, considering segments consisting of edges in an image, we derive an equation for optical flow. Then, making use of parallelism of line segments, we show that 3-D motion can be restored by using linear equations. To apply the algorithm there must exist two pairs of parallel line segments on an object. This paper presents an algorithm for extracting these pairs of parallel line segments. Finally, we verify the effectiveness of the algorithm by simulation.
We propose a digital optical arithmetic processor design based on symbolic substitution using holographic matched and space-invariant filters. The proposed system performs Boolean logic, binary addition, and subtracti...
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We propose a digital optical arithmetic processor design based on symbolic substitution using holographic matched and space-invariant filters. The proposed system performs Boolean logic, binary addition, and subtraction in a highly parallel manner; i.e., the processing time depends on word size but not array size. algorithms for performing binary addition and subtraction in parallel are presented. A skew problem occurring when symbolic substitution is applied to binary addition and subtraction with space-invariant systems is addressed, and its solution is suggested. Crosstalk in symbolic substitution is described, and new symbols which can prevent the crosstalk are introduced. System analysis and fundamental limitations of the proposed system are also presented in terms of processing time, overall light efficiency, and the maximum array size of the input data plane. The performance of the proposed system with that of the current electronic supercomputers has been compared by combining information about the processing time and maximum array size.
This paper describes an application of recurrent neural networks with feedback to the restoration of gray scale images corrupted by Gaussian disturbances. The two dimensional autoregressive (discrete homogeneous rando...
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ISBN:
(纸本)081940408X
This paper describes an application of recurrent neural networks with feedback to the restoration
of gray scale images corrupted by Gaussian disturbances. The two dimensional autoregressive (discrete
homogeneous random Gaussian-Markov field) model of gray scale images are considered and
identified as a base for future restoration. For the image restoration the concept of 2-D Kalman
filtering (with reduced update procedure) has been utilized. The 2-D Kalman filter for the image
restoration has been implemented as a tandem of two recurrent neural networks trained according
to the 2-D Kalman filtering algorithm.
The Fourier transforming properties of coherent imaging systems are well known and thoroughly developed. optical spatial filtering techniques for coherent imaging systems are also a well developed field of study. Most...
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ISBN:
(纸本)081940408X
The Fourier transforming properties of coherent imaging
systems are well known and thoroughly developed. optical spatial
filtering techniques for coherent imaging systems are also a well
developed field of study. Most of the advances in spatial
filtering techniques were developed for systems with a known set of
input characteristics. Once these filters were developed, they
were static and unable to change wih a new set of inputs
exhibiting a different set of characteristics. This paper will
present the theoretical basis and desiy of an adaptive coherent
imaging system using a two-dimensional spatial light modulator
(5124) in the frequency plane. A computer controller is used as a
feedback loop from the output plane back to the 5124. The filter
implemented by the SLM is developed by simulated annealing. This
iterative process enables the filter to adapt to a variety of
inputs and automatically optimize given sufficient iterations.
This paper will also present feasible applications of this
technique in image processing and pattern recognition.
An optical three-layer neural network and an associative network system for a semantic network using a microchannel plate spatial light modulator (MSLM) are described. In the optical three-layer neural network, the ba...
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ISBN:
(纸本)081940408X
An optical three-layer neural network and an associative network system for a semantic network using a microchannel plate spatial light modulator (MSLM) are described. In the optical three-layer neural network, the back-propagation learning algorithm is used to calculate optimum weight matrices. Experimental results on learning of exclusive OR operation are presented. In the optical implementation of the associative system, an MSLM is used to store an optimum weight matrix. The optimum weight matrix is calculated by a dynamic learning rule.
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