Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal imageprocessing. Linear filters generate a spatial distortion from initial image, what gives as result that speci...
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Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal imageprocessing. Linear filters generate a spatial distortion from initial image, what gives as result that specific algorithms are usually needed for each process with a complexity that cannot be implemented in vLSI systems for real time imageprocessing. MM overcome the inherent drawbacks of the linear processing based on the comparison of an initial image with some well-known geometric figures. In this paper we present the implementation of a specific processor that computes MM basic operations. Using a clock frequency of 250 MHz this processor is able to handle real time 512 X 512 pixels video images. MM allows non-linear processing of images and it is based on dilation and erosion operations using a geometric figure called structural element (SE). More complex imageprocessing can be performed using these two basic operations. In this implementation the SE of 3 X 3 pixels was chosen. 0.6 mum HGaAs standard cells technology, from vitesse Semiconductor Corporation, has been used achieving a logic level gate description with the possibility of migration to another technologies. (C) 2002 Elsevier Science Ltd. All rights reserved.
We study two classical connectivity-preserving parallel shrinking algorithms proposed to recognize and label two-dimensional connected components of binary images. The algorithms we consider were developed by Beyer [R...
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We study two classical connectivity-preserving parallel shrinking algorithms proposed to recognize and label two-dimensional connected components of binary images. The algorithms we consider were developed by Beyer [Recognition of topological invariants by iterative arrays, Ph.D. Thesis, MIT, 1969, p. 144] and Levialdi [Commun. ACM 15 (1) (1972) 7] independently for the purpose of shrinking 4-connected and 8-connected components of binary images in linear time, respectively. It is shown that those two independently developed algorithms are closely related and in a sense they are in a dual relation such that, for any initially given binary image and its inverted one, one algorithm produces, simultaneously, an image which is dual of the one produced by the other, step-by-step. (C) 2002 Elsevier Science B.v. All rights reserved.
This contribution describes a classification module integrated into an imageprocessing system consisting of a subsequent detection, tracking, and classification stage that extends its "knowledge" about a ce...
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This contribution describes a classification module integrated into an imageprocessing system consisting of a subsequent detection, tracking, and classification stage that extends its "knowledge" about a certain object class by autonomous in situ training. In our scenario, a classifier initially trained with front and rear views of pedestrians mainly in dark clothes subsequently extends its recognition capabilities in a first step towards lateral views of pedestrians in dark clothes, in a second step towards lateral views of pedestrians wearing both dark and bright clothes. Although supervised training algorithms are applied, at no point during the autonomous in situ training processes is an interaction with a human operator necessary;all training labels are autonomously generated by computing track-specific class assignments from time-step-specific class assignments. It is demonstrated that a significant improvement of the recognition performance with respect to new appearances, i.e., lateral views, of pedestrians, can be achieved without "forgetting" the initial front and rear views. (C) 2002 Elsevier Science B.v. All rights reserved.
Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal imageprocessing. Linear filters generate a spatial distortion from initial image, what gives as result that speci...
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Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal imageprocessing. Linear filters generate a spatial distortion from initial image, what gives as result that specific algorithms are usually needed for each process with a complexity that cannot be implemented in vLSI systems for real time imageprocessing. MM overcome the inherent drawbacks of the linear processing based on the comparison of an initial image with some well-known geometric figures. In this paper we present the implementation of a specific processor that computes MM basic operations. Using a clock frequency of 250 MHz this processor is able to handle real time 512 X 512 pixels video images. MM allows non-linear processing of images and it is based on dilation and erosion operations using a geometric figure called structural element (SE). More complex imageprocessing can be performed using these two basic operations. In this implementation the SE of 3 X 3 pixels was chosen. 0.6 mum HGaAs standard cells technology, from vitesse Semiconductor Corporation, has been used achieving a logic level gate description with the possibility of migration to another technologies. (C) 2002 Elsevier Science Ltd. All rights reserved.
Unequal loss protection with systematic Reed-Solomon codes allows reliable transmission of embedded multimedia over packet erasure channels. The design of a fast algorithm with low memory requirements for the computat...
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ISBN:
(纸本)0780376226
Unequal loss protection with systematic Reed-Solomon codes allows reliable transmission of embedded multimedia over packet erasure channels. The design of a fast algorithm with low memory requirements for the computation of an unequal loss protection solution is essential in real-time systems. Because the determination of an optimal solution is time-consuming, fast suboptimal solutions have been used. In this paper, we present a fast iterative improvement algorithm with negligible memory requirements. Experimental results for the JPEG2000, 2D, and 3D set partitioning in hierarchical trees (SPIHT) coders showed that our algorithm provided close to optimal peak signal-to-noise ratio (PSNR) performance, while its time complexity was significantly lower than that of all previously proposed algorithms.
As a rule, blur is a form of bandwidth reduction of an ideal image owing to the imperfect image formation process. It can be caused by relative motion between the camera and the original scene, or by an optical system...
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ISBN:
(纸本)0819444073
As a rule, blur is a form of bandwidth reduction of an ideal image owing to the imperfect image formation process. It can be caused by relative motion between the camera and the original scene, or by an optical system that is out of focus. Today there are different techniques available for solving of the restoration problem including Fourier domain techniques, regularization methods, recursive and iterative filters to name a few. But without knowing at cast approximate parameters of the blur, these filters show poor results. If incorrect blur model is chosen then the image will be rather distorted much more than restored. The original solution of the blur and blur parameters identification problem is presented in this paper. A neural network based on multi-valued neurons is used for the blur and blur parameters identification. It is shown that using simple single-layered neural network it is possible to identify the type of the distorting operator. Four types of blur are considered: defocus, rectangular, motion and Gaussian ones. The parameters of the corresponding operator are identified using a similar neural network. After a type of blur and its parameters identification the image can be restored using several kinds of methods. Some fundamentals of image restoration are also considered.
Digital Tv transmission systems allow a transmission channel to be shared by a number of sources. In order to improve the bandwidth utilization, variable bit rate encoding and statistical multiplexing techniques are u...
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ISBN:
(纸本)0780376226
Digital Tv transmission systems allow a transmission channel to be shared by a number of sources. In order to improve the bandwidth utilization, variable bit rate encoding and statistical multiplexing techniques are usually used. However, the channel sharing requires a careful scheduling method for multiplexing. This is because the video and audio materials have to be presented at the receivers at specific points in time. In this paper, we present a novel scheduling scheme for statistical multiplexing of vBR sources. Our method is sensitive to the timing requirements of the sources and sends the packets as close to their transmission deadlines as possible. The advantages of our method are: 1) it decreases the broadcast deadline violation probability (or improves the bandwidth utilization), 2) it minimizes the,delay and delay jitter of packets 3) it generates a transport stream compliant with all the standard Tv receivers. Simulations were conducted to compare our algorithm with the first-come-first-serve scheduling method. The results show that our algorithm significantly reduces both the percentage of dropped packets (by 35%-50%) and the average packet delay.
We study two classical connectivity-preserving parallel shrinking algorithms proposed to recognize and label two-dimensional connected components of binary images. The algorithms we consider were developed by Beyer [R...
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We study two classical connectivity-preserving parallel shrinking algorithms proposed to recognize and label two-dimensional connected components of binary images. The algorithms we consider were developed by Beyer [Recognition of topological invariants by iterative arrays, Ph.D. Thesis, MIT, 1969, p. 144] and Levialdi [Commun. ACM 15 (1) (1972) 7] independently for the purpose of shrinking 4-connected and 8-connected components of binary images in linear time, respectively. It is shown that those two independently developed algorithms are closely related and in a sense they are in a dual relation such that, for any initially given binary image and its inverted one, one algorithm produces, simultaneously, an image which is dual of the one produced by the other, step-by-step. (C) 2002 Elsevier Science B.v. All rights reserved.
Semantic analysis of cartographic images is interpreted as a separate representation of cartographic patterns (alphanumeric, punctual, linear, and area). We present an approach to map interpretation exploring the idea...
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ISBN:
(数字)9783540458685
ISBN:
(纸本)3540440666
Semantic analysis of cartographic images is interpreted as a separate representation of cartographic patterns (alphanumeric, punctual, linear, and area). We present an approach to map interpretation exploring the idea of synthesis of invariant graphic images at low level processing (vectorization and segmentation). This means that we ran "vectorization-recognition" and "segmentation-interpretation" systems simultaneously. Although these systems can generate some errors in interpretation, they are much more useful, for the following understanding algorithms because its output is nearly recognized objects of interest.
Many events are captured using multiple cameras today. Frames of each video stream have to be synchronized and aligned to a common time axis before processing them. Synchronization of the video streams necessarily nee...
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Many events are captured using multiple cameras today. Frames of each video stream have to be synchronized and aligned to a common time axis before processing them. Synchronization of the video streams necessarily needs a hardware based solution that is applied while capturing. The alignment problem between the frames of multiple videos can be posed as a search using traditional measures for image similarity. Multiview relations and constraints developed in Computer vision recently can provide more elegant solutions to this problem. In this paper, we provide two solutions for the video frame alignment problem using two view and three view constraints. We present solutions to this problem for the case when the videos are taken using affine cameras and for general projective cameras. Excellent experimental results are achieved by our algorithms.
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