The explosion of computational imaging has seen the frontier of imageprocessing move past linear problems, like denoising and deblurring, and towards non-linear problems such as phase retrieval. There has a been a co...
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ISBN:
(纸本)9781509015535
The explosion of computational imaging has seen the frontier of imageprocessing move past linear problems, like denoising and deblurring, and towards non-linear problems such as phase retrieval. There has a been a corresponding research thrust into non-linear image recovery algorithms, but in many ways this research is stuck where linear problem research was twenty years ago: Models, if used at all, are simple designs like sparsity or smoothness. In this paper we use denoisers to impose elaborate and accurate models in order to perform inference on generalized linear systems. More specifically, we use the state-of-the-art BM3D denoiser within the Generalized Approximate Message Passing (GAMP) framework to solve compressive phase retrieval. Our method demonstrates recovery performance equivalent to existing techniques using fewer than half as many measurements. This dramatic improvement in compressive phase retrieval performance opens the door for a whole new class of imaging systems.
image filtering is a key technology in imageprocessing applications for de-noising corrupted images. Digital images are often polluted by noise during capturing and hence they may not show the features or colors clea...
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ISBN:
(纸本)9781509006274
image filtering is a key technology in imageprocessing applications for de-noising corrupted images. Digital images are often polluted by noise during capturing and hence they may not show the features or colors clearly. image filtering removes the noise in an image and improves the contrast to provide better input for various imageprocessing applications. This paper proposes an efficient image filtering technique using fuzzy logic. The proposed method employs fuzzy membership functions in order to replace the noisy pixels based on the degree of membership of the neighboring pixels within a filter mask. Experimental results confirm that our method is very effective and fast for removing impulsive noise while preserving the small and sharp details in the image.
The paper analyzes well-known automated microscopy systems. The work presents the comparative analysis of low- and middle-designed algorithms. The adaptive module of pre-processing and image segmentation has been work...
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ISBN:
(纸本)9781509014149
The paper analyzes well-known automated microscopy systems. The work presents the comparative analysis of low- and middle-designed algorithms. The adaptive module of pre-processing and image segmentation has been worked out.
Current parallel programming frameworks aid to a great extent developers to implement applications in order to exploit parallel hardware resources. Nevertheless, developers require additional expertise to properly use...
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This paper proposes methods for detecting platoons in a traffic stream using automated techniques. Three different methods are tested for platoon detection, namely Cluster based approach, modified Gaur and Mirchandani...
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ISBN:
(纸本)9781509018901
This paper proposes methods for detecting platoons in a traffic stream using automated techniques. Three different methods are tested for platoon detection, namely Cluster based approach, modified Gaur and Mirchandani approach, and an imageprocessing based technique. Corroboration was carried out using dataset from an arterial in Chennai, India. The results obtained showed all the methods working well for platoon identification. The cluster based approach proved to work very well but it is an offline method for platoon identification. For real time environments, the modified G&M method as well as the imageprocessing solution showed promising results for the Indian traffic conditions with the modified G&M approach performing slightly better.
This paper describes and evaluates a novel 3D inspection system to detect anomalies in sewer pipes using stereo vision coupled with novel imageprocessingalgorithms. Currently, most commercial pipe inspection systems...
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ISBN:
(纸本)9781467386456
This paper describes and evaluates a novel 3D inspection system to detect anomalies in sewer pipes using stereo vision coupled with novel imageprocessingalgorithms. Currently, most commercial pipe inspection systems are designed with one or more Closed-circuit Television (CCTV) cameras. These systems are slow, costly and have limited accuracy (caused by human and environmental factors). More sophisticated systems (Laser-based, Infrared Thermography, Ultrasonic-based and Ground Penetrating Radar) suffer from: low resolution, high noise, high operational costs and an inability to detect water infiltration. The main objective of this research is to apply stereo vision and robust imageprocessing to generate 3D images of anomalies in sewer pipes in order to achieve high efficiency and accuracy for pipe inspection. The results show that various types of defects are successfully detectable. In addition, the correspondence time can be reduced by up to 45% and the accuracy of disparity maps is maintained compared to traditional local correspondence algorithms. Each component of the proposed system was tested individually with real and simulated data sets.
In such computerized systems, such as voice control units, personal identification, IP-telephony, weapon control commands, accepting applications for reference services, automated stenography, recognition of individua...
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In such computerized systems, such as voice control units, personal identification, IP-telephony, weapon control commands, accepting applications for reference services, automated stenography, recognition of individual words and phrases plays a major role in enhancing the effectiveness of technical systems..In the preliminary stages of speech processingalgorithms for the allocation of phonetic characteristics is implemented, which are subjected to syntactic and semantic analysis in subsequent *** isolate the phonetic characteristics acoustic treatment is performed, which includes algorithms of pre-filtering, spectral analysis, segmentation, and a calculation of cepstral *** this paper solves the problems of accelerated implementation of the acoustic processingalgorithms in realtime systems, in which there is recognition of the individual *** implement the stream computing is used opportunities of C++ programming language and Open MP *** perform stream computing algorithms are used dual-core and multi-core *** results of acceleration calculations correspond to the number of processor cores.
This paper introduces a linear in the parameter model for Homomorphic filter using Volterra series approach. To obtain these parameters we propose a model where we choose a sub image from the response of Homomorphic f...
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This paper introduces a linear in the parameter model for Homomorphic filter using Volterra series approach. To obtain these parameters we propose a model where we choose a sub image from the response of Homomorphic filter as reference image to reduce computational complexity. We apply non uniform illuminated images to the proposed filter and compare its performance against standard Homomorphic filter. The proposed filter outperforms the traditional Homomorphic filter in all experiments. Also we compare the error convergence and steady-state error of Sparse aware LMS with LMS algorithm to calculate proposed filter coefficients.
Pedestrian segmentation in infrared images is a difficult problem for the defects of low SNR and inhomogeneous luminance distribution. In this paper, we propose a method which aims to obtain the accurate pedestrian se...
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ISBN:
(纸本)9781467399623
Pedestrian segmentation in infrared images is a difficult problem for the defects of low SNR and inhomogeneous luminance distribution. In this paper, we propose a method which aims to obtain the accurate pedestrian segmentation through a background prior and boundary weight-based saliency. Background likelihood is firstly calculated as background prior to get an abstract representation for infrared pedestrian. Then, by considering the object-center prior, the object-biased Gaussian model is applied to derive the probability density estimation for pedestrians. Finally, the above two results are integrated with the boundary weight to obtain the final saliency map for infrared image, based on which pedestrians can be easily segmented. Experimental results on real infrared images captured by intelligent transportation systems demonstrate the effectiveness of the proposed approach against the state-of-the-art algorithms.
This paper presents an FPGA based real-time lane detection system for automotive applications. To reduce the computational complexity, the conventional Canny-Hough lane detection algorithm is modified for achieving th...
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ISBN:
(纸本)9781509015719
This paper presents an FPGA based real-time lane detection system for automotive applications. To reduce the computational complexity, the conventional Canny-Hough lane detection algorithm is modified for achieving the real-time processing. The prototype design is realized by using the commercialized FPGA platform and the processing rate is enhanced by 41% compared to the previous detection algorithm.
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