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ANALOG 2016;15. ITG/GMM-Symposium

作者： Christopher Soell Timo Mai Lan Shi Juergen Roeber Thomas Ussmueller Robert Weigel Amelie Hagelauer Institute for Electronics Engineering FAU Erlangen-Nuremberg Institute for Mechatronics University of Innsbruck

In this work, a low-power high-gain operational amplifier is presented, which is dedicated to work in an analog image pre-processing stage in a smart sensor system. This stage is able to detect edges and shapes for instance, before the image is passed to the ADC and the digital computation stage, reducing data and precision requirement of both stages. This approach helps to save power, making smart image sensor nodes with energy harvesting reasonable. Since the precision as well as the energy consumption of the edge detection algorithm is highly depended on the amplifier used for the basic summing and multiplier blocks, the design of it plays an important role for the approach. The proposed input/output rail-to-rail operational amplifier is based on a 150 nm CMOS technology, has a gain of 77 dB and a unity gain bandwidth of 45.7 MHz while consuming only 77 muA statically at a supply voltage of 1.8 V.

关键词： Amplifiers Operational amplifiers analog image boundary detection algorithm gain bandwidth intelligent sensors supply voltage high gain LOW POWER Multiplying circuits CMOS technology Precision Sensor systems

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Fast detection of Curved Edges at Low SNR

Fast Detection of Curved Edges at Low SNR

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Nati Ofir Meirav Galun Boaz Nadler Ronen Basri Weizmann Institute of Science

ISBN: (纸本)9781467388528

Detecting edges is a fundamental problem in computer vision with many applications, some involving very noisy images. While most edge detection methods are fast, they perform well only on relatively clean images. Unfortunately, sophisticated methods that are robust to high levels of noise are quite slow. In this paper we develop a novel multiscale method to detect curved edges in noisy images. Even though our algorithm searches for edges over an exponentially large set of candidate curves, its runtime is nearly linear in the total number of image pixels. As we demonstrate experimentally, our algorithm is orders of magnitude faster than previous methods designed to deal with high noise levels. At the same time it obtains comparable and often superior results to existing methods on a variety of challenging noisy images.

关键词： images Noise levels low SNR Noisy Image Noise curve edge computer vision Curved edges Edges boundary detection algorithm Fasting Runtime

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IMPROVING SENSOR NOISE ANALYSIS FOR CT-SCANNER IDENTIFICATION

IMPROVING SENSOR NOISE ANALYSIS FOR CT-SCANNER IDENTIFICATIO...

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European Signal Processing Conference

作者： Anas Kharboutly William Puech Gerard Subsol Denis Hoa ICAR Research Team LIRMM University of Montpellier/CNRS IMAIOS MIBI

ISBN: (纸本)9781479988518

CT-Scanner devices produce three-dimensional images of the internal structure of the body. In this paper, we propose a method that is based on the analysis of sensor noise to identify the CT-Scanner device. For each CT-scanner we built a reference pattern noise and a correlation map from its slices. Finally, we can correlate any test slice with the reference pattern noise of each device according to its correlation map. This correlation map gives a weighting for each pixel regarding its position in the reference pattern noise. We used a wavelet-based Wiener filter and an edge detection method to extract the noise from a slice. Experiments were applied on three CT-Scanners with 40 3D images, including 3600 slices, and we demonstrate that we are able to identify each CT-Scanner separately.

关键词： Digital forensics Medical image forensics Authentication Device identification Noise pattern Sensor noise Denoise filtering Edge detection Wavelet transformation E-discovery wavelet transforms Edge detection modal noise Authentication boundary detection algorithm Noise Three-Dimensional Images slicing general structure Sensors Wiener filters

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Cut Scene Change detection Using Spatio Temporal Video Frame

Cut Scene Change Detection Using Spatio Temporal Video Frame

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International Conference on Image Information Processing

作者： Rupesh Kumar Sumana Gupta K. S. Venkatesh Dept. of Electrical Engineering Indian Institute of Technology

ISBN: (纸本)9781509001491

In this paper, we addressed the problem of cut or abrupt scene change detection in video sequence. Video is defined as a sequence of XY frame with flow direction T. Proposed method considered spatio-temporal frames TY and TX for detection. In XY frame, large pixel intensity variation occurred at the location of cut scene change and such phenomena produced a boundary line in spatio-temporal frames. Proposed boundary appeared as a vertical line for each scene change. Each scene categorizes as an uniform region and their transition produces a boundary line. These boundary has been detected with the help of edge detection method in both TY and TX frames simultaneously, A two way detection in TY and TX frames confirms the accuracy of detection algorithm and eliminates the false detection.

关键词： Video frame boundary: spatio-temporal Scene Segmentation Shot Cut VIDEO FRAMES ON-SCENE Cutting Frame segmentation Segmentation FRAMES boundary detection algorithm shot vertical line detection algorithms

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The furthest neighbor query of space K

The furthest neighbor query of space K

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Cheng Chang Run-Tao Liu Department of applied mathematics Harbin University of Science and Technology Institute of information and scientific computing technology Harbin University of Science and Technology

ISBN: (纸本)9781467372251

In the spatial database, the furthest neighbor query is a jumped-up method. If different distances and pruning strategies are properly selected, we can greatly reduce the node number in search space. Through using data cube and edge detection method, we catch up with the traverse pruning method that is based on FNC spatial index tree of incremental and query algorithms. The experimental result turns out that the algorithms have a good pruning effect, at the same time promoting the query efficiency of space k farthest neighbors.

关键词： database indexing edge detection query processing search problems trees (mathematics) visual databases FNC spatial index tree data cube edge detection method furthest neighbor query incremental algorithms jumped-up method node number pruning effect pruning strategies query algorithms query efficiency search space space k farthest neighbors spatial database traverse pruning method FNC-Tree Spatial databases Sub cube The furthest neighbor query visual databases boundary detection algorithm database indexing tabu search query analysis Edge detection data cubes Neighbor

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Edge detection Method of Gaussian Block Distance

Edge Detection Method of Gaussian Block Distance

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IEEE International Conference on Image Processing

作者： Di JIA Cheng-long XIAO Jin-guang SUN School of Electronic and Information Engineering Liaoing Technical University School of software Liaoing Technical University

ISBN: (纸本)9781479983407

Edge is one of the most important image features, and it is the base of follow-up measurement and shape registration. In order to get better edge information, an edge detection method of block distance is proposed in this paper. Firstly, by calculating distance between the pixels within sub-block regions, the graph of Gaussian weighted distance is obtained. Comparing with the original figure, it not only can better highlight the edge contour, but also can be uniformed background gray. Secondly, in order to reduce the complexity of the algorithm, edge detection method of block distance combining with summed area table is raised. Finally, implementation process of this algorithm is raised. Experimental results show that this method can achieve high speed of edge detection with higher accuracy in extracting edge and corner information of image.

关键词： Edge detection Euclidean distance Gaussian block distance Summed area table Distance map boundary detection algorithm Edge detection Euclidean distance image feature Edge of a figure or solid Gauss

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Efficient Morphological-based Edge detection algorithm for Computed Tomography Cardiac Images

Efficient Morphological-based Edge Detection Algorithm for C...

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IEEE International Conference on Signal and Image Processing Applications

作者： Thion Ming Chieng Zaid Omar Suhaini Kadiman IJN-UTM Cardiovascular Engineering Centre Universiti Teknologi Malaysia Johor Malaysia IJN-UTM Cardiovascular Engineering Centre National Heart Institute Kuala Lumpur Malaysia

ISBN: (纸本)9781479989973

Medical imaging has been extensively used for disease monitoring, treatment planning, diagnosis and computer aided surgery. Often, the acquired images are raw in nature, thus making them prone to being complex and noisy. A series of preprocessing and information extraction steps are therefore necessary in order for the relevant information to reach the medical practitioner. To this end, image denoising and edge detection play a vital role as a precursor to more advanced techniques in the medical image processing field. In this paper we have proposed an innovative mathematical morphology-based image denoising and edge detection method, for pre-processing of computed tomography (CT) images of the human heart. The morphological edge detection algorithm together with six different shaped structuring elements are implemented to preserve and detect the edges of the CT image while effectively suppressing noise, all at low computational cost. The experimental results affirm our approach's efficiency and capability in denoising and detecting salient edges from corrupted and complex medical images.

关键词： Medical imaging cardiac image Computed tomography Morphology denoising Edge detection Medical imaging Edge detection boundary detection algorithm Noise reduction X-Ray Computed Tomography image denoising images medical practitioner

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A novel image edge detection algorithm based on neutrosophic set

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COMPUTERS & ELECTRICAL ENGINEERING 2014年第8期40卷 3-25页

作者： Guo, Yanhui Sengur, Abdulkadir St Thomas Univ Sch Sci Miami Gardens FL 33054 USA Firat Univ Fac Technol Dept Elect & Elect Engn TR-23169 Elazig Turkey

Neutrosophic set (NS) theory is a formal framework to study the origin, nature, and scope of the neutral state. In this paper, neutrosophic set is applied in image domain and a new directional alpha-mean operation is defined. Based on this operation, neutrosophic set is applied into image edge detection procedure. First, the image is transformed into NS domain, which is described by three membership sets: T, I and F. Then, a directional alpha-mean operation is employed to reduce the indeterminacy of the image. Finally, a neutrosophic edge detection algorithm (NSED) is proposed based on the neutrosophic set and its operation to detect edge. Experiments have been conducted using numerous artificial and real images. The results demonstrate the NSED can detect the edges effectively and accurately. Particularly, it can remove the noise effect and detect the edges on both the noise-free images and the images with different levels of noises. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： noise-free Edge detection boundary detection algorithm images indeterminancy Image Noise effects Surgery

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Semiautomatic interpretation of microgravity data from subsurface cavities using curvature gradient tensor matrix

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NEAR SURFACE GEOPHYSICS 2014年第5期12卷 579-586页

作者： Zhou, Wenna Li, Jiyan Du, Xiaojuan Jilin Univ Coll Geoexplorat Sci & Technol Changchun 130026 Jilin Peoples R China Jilin Univ Coll Earth Sci Changchun 130061 Jilin Peoples R China

We propose an effective technique, based on eigenvalues of the curvature gradient tensor matrix (CGTM), to determine edges and depths of shallow subsurface cavities. The new technique is similar to the tilt angle and tilt-depth methods in edge detection and depth estimation, respectively. Our improvement to this method is that the vertical derivative of the tilt angle is replaced by an eigenvalue of the CGTM. Zero contours of eigenvalues of the CGTM can be used to outline the edges of causative sources, and the characteristic is similar to the vertical derivative of gravity field. Therefore, we use the smaller of the two eigenvalues to replace the vertical derivative in the numerator of the tilt angle, and this results in an improved edge detection method. In addition, we deduce a new depth estimation method using the point mass model parameters which can be used to estimate the centre depths of shallow causative sources. The new method is tested on a synthetic model with and without noise. It demonstrates that the new method is simple, robust and accurate. Finally, we apply the method on the measured gravity data of a mining subsidence area from Liaoyuan, Northeast of China. The results show a good correspondence with the inversion results of electrical resistivity tomography (ERT) data. Such results can serve as preliminary depth estimates and location of near surface cavities.

关键词： TILT Edge detection boundary detection algorithm gravitational fields Gravity data Angle eigenvalues Numerator vertical

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Fast and Accurate Implementation of Canny Edge Detector on Embedded Many-core Platform 12

Fast and Accurate Implementation of Canny Edge Detector on E...

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12th IEEE International New Circuits and Systems Conference (IEEE NEWCAS)

作者： Ben Cheikh, Taieb Lamine Nicolescu, Gabriela Trajkovic, Jelena Bouchebaba, Youcef Paulin, Pierre Ecole Polytech Dept Comp Engn Montreal PQ Canada Concordia Univ Dept Elect & Comp Engn Montreal PQ H3G 1M8 Canada Synopsys Inc Ottawa ON Canada

ISBN: (纸本)9781479948857

Image processing and computer vision applications are used intensively in several domains in particular multimedia and medicine. The main challenge in developing such applications is how to guarantee both high accuracy and low execution time. Accordingly, we observe two research directions: the first focuses on improving the algorithms and the second focuses on designing fast hardware platforms. In this paper, we propose an efficient parallel implementation of an accurate extended Canny edge detection algorithm suitable for medical applications on embedded many-core platform. The proposed implementation is running at a frame rate of 10 frames/s for image size of 512x512 with high accurate and smooth line edges.

关键词： Accuracy Computer architecture Fabrics Graphics processing units Hardware Image edge detection Real-time systems Edge detection Computer Architecture real-time systems Canny edge detector Textile fabrics fabric Computer hardware Graphics Processing Unit boundary detection algorithm Fasting Frame Rate IMAGE SIZE

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