The goal of this project is to improve the performance of the parallel computer SYMPATI2. This SIMD processor based system performs with a good efficiency the low level imageprocessing operations, but this efficiency...
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The goal of this project is to improve the performance of the parallel computer SYMPATI2. This SIMD processor based system performs with a good efficiency the low level imageprocessing operations, but this efficiency is drastically cut when handling an intermediate level class of algorithms. This study emphasis the drawbacks encountered to perform such operations. The main one is the interconnection between processors. So, a new interconnection network, called the open intelligent network, is proposed and added to SYMPATI2 to form SYMPATIX. This network detailed below allows irregular transfers of data between the different processing elements of the new system. Furthermore, this network allows the efficient interconnection of specific modules. In this paper, the architecture is evaluated on representative algorithms of imageprocessing. Then, a behavioural model of SYMPATIX is described using a hardware description language, the VHDL. Our SIMD computer efficiency has been considerably upgraded for the low and intermediate levels of imageprocessing. Furthermore, its application area was extended. The last part of the paper describes the performance obtained with simulations.
image reconstruction algorithms for computerized tomography are of interest for both medical and industrial applications. The special geometry of these image reconstruction applications can be used to implement optima...
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image reconstruction algorithms for computerized tomography are of interest for both medical and industrial applications. The special geometry of these image reconstruction applications can be used to implement optimal reconstruction algorithms, such as the minimum variance estimator, in a computationally efficient manner which could become competitive with popular approximate algorithms. As a result of measurement acquisition procedures of typical CT configurations, both fan-beam and parallel-beam arrangements lead to circulant matrix forms which can be used as the basis for fast algorithms. The general minimum variance estimator for this application is reviewed, and a fast algorithm is presented which uses Fourier Transform techniques.
image analysis is an important requirement of many artificial intelligence systems. Though great effort has been devoted to inventing efficient algorithms far image analysis, there is still much work to be done. It is...
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ISBN:
(纸本)0819437654
image analysis is an important requirement of many artificial intelligence systems. Though great effort has been devoted to inventing efficient algorithms far image analysis, there is still much work to be done. It is natural to turn to mammalian vision systems for guidance because they are the best known performers of visual tasks. The pulse-coupled neural network (PCNN) model of the cat visual cortex has proven to have interesting properties for imageprocessing. This article describes the PCNN application to the processing of images of heterogeneous materials;specifically PCNN is applied to image denoising and image segmentation. Our results show that PCNNs do well at segmentation if we perform image smoothing prior to segmentation. We use PCNN for both smoothing and segmentation. Combining smoothing and segmentation enable us to eliminate PCNN sensitivity to the setting of the various PCNN parameters whose optimal selection can be difficult and can vary even for the same problem. This approach makes imageprocessing based on PCNN more automatic in our application and also results in better segmentation.
Still-imageprocessingalgorithms are tailored to and depend crucially upon the properties of the class of images to which they are applied, for instance natural images in consumer digital cameras, medical images in f...
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ISBN:
(纸本)9781424456536
Still-imageprocessingalgorithms are tailored to and depend crucially upon the properties of the class of images to which they are applied, for instance natural images in consumer digital cameras, medical images in fMRI machines, and binary text images in some photocopiers. We describe a new and possibly very important class of images and tasks for which traditional algorithms seem ill-suited, and for which new algorithms and general methods and concepts are required. This new class of images arises in imaging systems designed through new, joint optimization methods where the optics and the imageprocessing are designed simultaneously in order to yield a high-quality digital image. These new design methods yield intermediate optical images that have unusual spatial, noise and chromatic properties ill-served by traditional image methods. Moreover, these new images present a number of novel challenges in imageprocessing hardware implementations such as constrained space-variance. We describe these briefly new, joint methods for designing digital-optical imaging systems, characterize the intermediate optical images they yield, and some of the digital imageprocessing challenges for producing high-quality still images from these sensed optical images.
Accurate vehicle detection plays a vital role in intelligent transportation systems. Various day conditions, for instance, dawn, morning, noon, or non-uniform illuminations put restrictions on camera's visibility....
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Accurate vehicle detection plays a vital role in intelligent transportation systems. Various day conditions, for instance, dawn, morning, noon, or non-uniform illuminations put restrictions on camera's visibility. Such scenarios impact the performance of detection and recognition algorithms that are used in surveillance systems and autonomous driving. This paper aims to solve the aforementioned issues using machine learning methods, such as face detection and recognition. The core theme of this paper is the development of a vehicle detection and driver recognition system, which also focuses the situation where an input image is degraded by non-uniform illuminations. The proposed system is composed of four main processing modules: (i) image acquisition, (ii) image enhancement, (iii) object detection that locates vehicles' and drivers' faces, and (iv) the Pool of Face Recognition algorithms (PoFRA), which uses four face recognition algorithms to conclude the driver's identity. We implement suitable algorithms for each of the above-described modules to appraise its practicability. The system can be adjusted to work in different types of extreme weather conditions, such as strong or dim light. Experimental results demonstrate that the proposed system has significant potential to take the research on automated car parking systems to the next level.
This paper presents a method to exploit rank statistics to improve fully automatic tracing of neurons from noisy digital confocal microscope images. Previously proposed exploratory tracing (vectorization) algorithms w...
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This paper presents a method to exploit rank statistics to improve fully automatic tracing of neurons from noisy digital confocal microscope images. Previously proposed exploratory tracing (vectorization) algorithms work by recursively following the neuronal topology, guided by responses of multiple directional correlation kernels. These algorithms were found to fail when the data was of lower quality (noisier, less contrast, weak signal, or more discontinuous structures). This type of data is commonly encountered in the study of neuronal growth on microfabricated surfaces. We show that by partitioning the correlation kernels in the tracing algorithm into multiple subkernels, and using the median of their responses as the guiding criterion improves the tracing precision from 41% to 89% for low-quality data, with a 5% improvement in recall. Improved handling was observed for artifacts such as discontinuities and/or hollowness of structures. The new algorithms require slightly higher amounts of computation, but are still acceptably fast, typically consuming less than 2 seconds on a personal computer (Pentium iii, 500 MHz, 128 MB). They produce labeling for all somas present in the field, and a graph-theoretic representation of all dendritic/axonal structures that can be edited. Topological and size measurements such as area, length, and tortuosity are derived readily. The efficiency, accuracy, and fully-automated nature of the proposed method makes it attractive for large-scale applications such as high-throughput assays in the pharmaceutical industry, and study of neuron growth on nano/micro-fabricated structures. A careful quantitative validation of the proposed algorithms is provided against manually derived tracing, using a performance measure that combines the precision and recall metrics. Index Terms-Biomedical imageprocessing, image analysis, image edge analysis, image line pattern analysis, imageprocessing, image segmentation, median filters.
Color imageprocessing in machine vision systems has not gained general acceptance. Most machine vision systems use images that are shades of gray. The Laser Automated Decoating System (LADS) required a vision system ...
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ISBN:
(纸本)0819416886;9780819416889
Color imageprocessing in machine vision systems has not gained general acceptance. Most machine vision systems use images that are shades of gray. The Laser Automated Decoating System (LADS) required a vision system which could discriminate between substrates of various colors and textures and paints ranging from semi-gloss grays to high gloss red, white and blue (Air Force Thunderbirds). The changing lighting levels produced by the pulsed CO 2 laser mandated a vision system that did not require a constant color temperature lighting for reliable image analysis.
A Toeplitz-block-Toeplitz (TBT) matrix is block Toeplitz with Toeplitz blocks. TBT systems of equations arise in 2-D interpolation, 2-D linear prediction and 2-D least-squares deconvolution problems. Although the doub...
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ISBN:
(纸本)0780370414
A Toeplitz-block-Toeplitz (TBT) matrix is block Toeplitz with Toeplitz blocks. TBT systems of equations arise in 2-D interpolation, 2-D linear prediction and 2-D least-squares deconvolution problems. Although the doubly Toeplitz structure should be exploitable in a fast algorithm, existing fast algorithms only exploit the block Toeplitz structure, not the Toeplitz structure of the blocks. Iterative algorithms can employ the 2-D FFT, but usually take thousands of iterations to converge. We develop a new fast algorithm that assumes a smoothness constraint (described in the text) on the matrix entries. For an M-2 X M-2 TBT matrix with M M x M Toeplitz blocks along each edge, the algorithm requires only O(6M(3)) operations to solve an M-2 X M-2 linear system of equations;parallel computing on 2M processors can be performed on the algorithm as given. Two examples show the operation and performance of the algorithm.
Two algorithms are presented for the detection of gradual transitions in video sequences. The first is a dissolve detection algorithm utilizing certain properties of a dissolve's trajectory in image-space. The sec...
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ISBN:
(纸本)0780362985
Two algorithms are presented for the detection of gradual transitions in video sequences. The first is a dissolve detection algorithm utilizing certain properties of a dissolve's trajectory in image-space. The second is an algorithm to detect a wide variety of wipes based on image histogram characteristics during such transitions. Both algorithms operate in the compressed domain, requiring only partial decoding of the compressed video stream. Experiments show the algorithms perform well in detecting a wide variety of gradual transitions, and at a significant reduction in computation time when compared with full-frame methods.
The discrete system mathematical model with casual chaotic structure for algorithms synthesis to radar-tracking coherent and noncoherent images of spreading surface is investigated. Discrete systems with casual chaoti...
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ISBN:
(纸本)9780819467270
The discrete system mathematical model with casual chaotic structure for algorithms synthesis to radar-tracking coherent and noncoherent images of spreading surface is investigated. Discrete systems with casual chaotic structure are understood observably in the discrete moments of time as stochastic dynamic systems which structure has final number of possible conditions, varied each other at the casual moments of time. Radar images processing (segmentation) by two new algorithms in remote distance problems applications are discussed.
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