NASA Technical Reports Server (Ntrs) 19850014758: New Atmospheric Sensor Analysis Study by NASA Technical Reports Server (Ntrs); NASA Technical Reports Server (Ntrs); published by
NASA Technical Reports Server (Ntrs) 19850014758: New Atmospheric Sensor Analysis Study by NASA Technical Reports Server (Ntrs); NASA Technical Reports Server (Ntrs); published by
[Auto Generated] RESEARCH SUMMARY AND OVERVIEW 2 PROJECT REPORTS I. image SEGMENTATION 1. image Decomposition 7 by T. 5. Huang and J. W. Burnett 2. Digital Edge Restoration in Linearly Filtered images 12 by D. P. Pand...
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[Auto Generated] RESEARCH SUMMARY AND OVERVIEW 2 PROJECT REPORTS I. image SEGMENTATION 1. image Decomposition 7 by T. 5. Huang and J. W. Burnett 2. Digital Edge Restoration in Linearly Filtered images 12 by D. P. Panda and A. C. Kak 3. image Segmentation by Unsupervised Clustering III 2k by M. Y. Yoo and T. S. Huang **. Texture Boundary Detection 27 by 0. R. Mitchell and W. K. Chan I I. image ATTRIBUTES 5. Max-Min Measure for image Texture Analysis 29 by 0. R. Mitchell and W. A. Boyne III. PATTE
In this paper, design and development of a selfsufficient sentry robotic gun is presented. Professional robotic assemblies which are generally developed for security purposes are targeted toward high efficiency and ar...
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ISBN:
(纸本)9781509040599
In this paper, design and development of a selfsufficient sentry robotic gun is presented. Professional robotic assemblies which are generally developed for security purposes are targeted toward high efficiency and are based on extensive control algorithms. This makes them quite expensive and infeasible for low budget applications. One important component of such systems is that of motion detection. Motion detection also plays a key role in security applications installed at banks, offices and vulnerable areas. An efficient motion detection system has been developed using embedded micro-controller and MATLAB interface. The proposed system can also be set into an autonomous mode of operation, in which the system tracks and engages targets without any human intervention. Aside from autonomous mode, there is also a manual over-ride mode. The hardware employed in the proposed system is based on easily accessible materials. Motion detection and imageprocessing was implemented using MATLAB imageprocessing toolbox and periodic background estimation subtraction was used for the detection of motion.
In this paper, we propose a novel method for detecting and recognizing the text from the blurred images. Text detection in natural scenery images is an important issue in the processing stage. All the previously propo...
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ISBN:
(纸本)9788132226710;9788132226697
In this paper, we propose a novel method for detecting and recognizing the text from the blurred images. Text detection in natural scenery images is an important issue in the processing stage. All the previously proposed methods use different algorithms to detect text in images;however, they suffer from poor performance while performing detection in blurred images. The proposed algorithm is capable of removing blur with an iterative deconvolution method and a linear invariant filter. The proposed method can achieve detection and recognition of the text with a time complexity of 4.53 s. Experiments show our method achieves a better text detection than the other existing methods.
To provide an accurate surface defects inspection method and make the automation of robust image region of interests(ROI) delineation strategy a reality in production line, a multi-source CCD imaging based fuzzy-rough...
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ISBN:
(数字)9781510603349
ISBN:
(纸本)9781510603332;9781510603349
To provide an accurate surface defects inspection method and make the automation of robust image region of interests(ROI) delineation strategy a reality in production line, a multi-source CCD imaging based fuzzy-rough sets method is proposed for hot slab surface quality assessment. The applicability of the presented method and the devised system are mainly tied to the surface quality inspection for strip, billet and slab surface etcetera. In this work we take into account the complementary advantages in two common machine vision (MV) systems(line array CCD traditional scanning imaging (LS-imaging) and area array CCD laser three-dimensional (3D) scanning imaging (AL-imaging)), and through establishing the model of fuzzy-rough sets in the detection system the seeds for relative fuzzy connectedness(RFC) delineation for ROI can placed adaptively, which introduces the upper and lower approximation sets for RIO definition, and by which the boundary region can be delineated by RFC region competitive classification mechanism. For the first time, a Multi-source CCD imaging based fuzzy-rough sets strategy is attempted for CC-slab surface defects inspection that allows an automatic way of AI algorithms and powerful ROI delineation strategies to be applied to the MV inspection field.
This paper proposes an efficient method to improve image quality based on Context-based enhancement techniques, particularly towards real-time applications in dedicated hardware systems. The main idea is that all the ...
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Digital photography has experienced great progress during the past decade. A lot of people are recording their moments via digital hand-held cameras. Pictures taken with digital cameras usually undergo some sort of de...
Digital photography has experienced great progress during the past decade. A lot of people are recording their moments via digital hand-held cameras. Pictures taken with digital cameras usually undergo some sort of degradation in the form of noise/blur depending on the camera hardware and environmental conditions in which the photos are taken. This leads to an ever-increasing demand for effective and efficient image enhancement algorithms to achieve high quality output images in digital photography systems. In this dissertation, a new graph-based framework is introduced for different image restoration applications. This framework is based on exploiting the existing self-similarity in images. We introduce a new definition of normalized graph Laplacian matrix for imageprocessing. We use this new definition to develop effective enhancement algorithms for image deblurring, image denoising, and image sharpening. First, we develop a regularization framework for image deblurring by constructing a new graph-based cost function. Minimizing the corresponding cost function yields effective outputs for different blur types including out-of-focus and motion blurs. Our proposed deblurring algorithm based on the new definition of normalized graph Laplacian provides performance and analysis advantages over previous methods. We have shown its effectiveness for several synthetic and real deblurring examples. Second, we develop a new graph-based framework for image denoising. The proposed denoising method exploits the similarity information in images by constructing the similarity matrix which in turn is used to derive the corresponding graph Laplacian. A graph-based objective function with new data fidelity and smoothness terms is constructed and minimized. We also establish the relationship between our proposed regularized framework and two well-known iterative methods for improving the performance of kernel-based denoising methods; namely, diffusion and boosting iterations. We com
In recent years, sparse approximation has played a fundamental role in many signal processing areas. The sparsity-induced regularization methods for image recovery are implemented based on the assumption that the unde...
In recent years, sparse approximation has played a fundamental role in many signal processing areas. The sparsity-induced regularization methods for image recovery are implemented based on the assumption that the underlying images can be sparsely approximated under the given system. Herein, over-complete systems, especially tight frames, possess advantages in sparse image representation and have been widely used in applications. In the first part of this dissertation, we focus on constructing discrete (tight) frames using Gabor atoms to meet the needs for sparse image modeling. Gabor systems have many advantages in sparse representation, for example accurate local time-frequency analysis and strong orientation selectivity. However, the discretiza- tion of continuous Gabor frames is non-trival in the sense that the resulted discrete system may lose the frame property, as well as fast implementation algorithms. Mo- tivated by these, we study the general theory of discrete Gabor frames by developing Gramian and dual Gramian analysis in C N. Consequently, we derive a necessary and sufficient condition for discrete tight Gabor frames and construct two classes of discrete tight Gabor frames as examples. Further, to remove the non-zero DC (di- rect current) offset, we revise the tight Gabor frame to Gabor induced frames with closed-form dual frames and the decomposition and recontruction processes can be implemented via filter bank based fast algorithms. The orientation selectivity of the resulted Gabor induced frame is optimal, i. e. the associated filters provide all the possible directions defined on discrete uniform grid. A weakness of the Gabor system is that it lacks the multi-scale property since all its atoms are of fixed size. One way to solve this problem is to consider multi-scale Gabor frames composed of several Gabor frames with windows of various lengths. The other way is to construct tight frame with both Gabor and MRA structures. Specifically, we take a set
This paper describes the optical setup and imageprocessing required to estimate melt-pool width and build height for real-time control of melt-pool geometry in directed energy deposition additive manufacturing. To ov...
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