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10th International Conference on Natural Computation (ICNC)

作者： Hao, Deshui Ji, Luping Zhou, Long Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu Peoples R China

ISBN: (纸本)9781479951512

This paper presents a rapid edge detection method for vehicle using the two-dimensional cellular neural network (CNN). In the method, two adaptive templates for edge detection are experimentally designed, and background noise elimination is also concerned. Finally, the performance of the proposed CNN detector is evaluated on different vehicle images, and it is also compared with some other edge detectors. Simulation experiment results shows that the CNN method could achieve good performance in vehicle edge detection.

关键词： Cellular neural networks Detectors Digital images Image edge detection Noise Particle swarm optimization Vehicles Edge detection Cellular neural networks vehicle Digital images Particle swarm optimization Noise boundary detection algorithm detector

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Efficient Bone Detector and Geometric Descriptor for X-ray Imaging

Efficient Bone Detector and Geometric Descriptor for X-ray I...

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IEEE Symposium Series on Computational Intelligence

作者： Jakub Romanowski Marcin Korytkowski Rafal Scherer Institute of Computational Intelligence Czestochowa University of Technology

ISBN: (纸本)9781479975617

detection of bone area in X-ray images and methods of comparing such images on the basis on their content is still an issue which can be substantially improved. In this paper we present a new method of efficient bone identification and its description by a collection of simple geometrical shapes. The idea of this kind of bones description was to developed a method that could reduce the amount of data to minimum. The solution enables fast comparison of X-ray images by checking small amount of data. This kind of geometric description of bone area is designed to create a robust bone descriptor which will be used as image pattern for image comparison method. The assumption is to create a descriptor of X-ray digital image content, mining them in large databases and search and compare X-ray images on the basis of their content. The achievement of the objectives was possible through the use of an edge detection method modified by the authors. Application of our method of edge detection gives much more satisfactory results and possibilities to further process medical images than commonly used methods of edge detection.

关键词： bone structure Edge detection images boundary detection algorithm Descriptors X-ray imaging X-rays

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Transparent text detection and background recovery

Transparent text detection and background recovery

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2nd IAPR Asian Conference on Pattern Recognition (ACPR)

作者： Liu, Xinhao Chiba, Naoki Tokyo Inst Technol Grad Sch Sci & Engn Tokyo 152 Japan Rakuten Inc Rakuten Inst Technol Tokyo Japan

ISBN: (纸本)9781479921904

We propose two methods for detecting transparent text in images and recovering the background behind the text. Although text detection in natural scenes is an active research area, most current methods are focused on non-transparent text. To detect transparent text, we developed an adaptive edge detection method for edge-based text detection that can accurately detect text even under low contrast, which is common among transparent text images and a method for recovering the original background content behind the detected transparent text. Experiments using real images show the effectiveness of the proposed methods.

关键词： texts Hyalin natural scenes boundary detection algorithm images

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SAR image despeckling in directionlet domain based on edge detection

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ELECTRONICS LETTERS 2013年第6期49卷 422-423页

作者： Sethunadh, R. Thomas, T. Indian Space Res Org Trivandrum 695022 Kerala India Cochin Univ Sci & Technol Cochin 682022 Kerala India

Presented is a novel directionally adaptive despeckling algorithm for a SAR image using a multi-direction anisotropic wavelet transform, called a directionlet. It efficiently extracts edge information along dominant directions from the spatially segmented SAR image. Then an optimal scale dependent subband adaptive threshold, based on the generalised cross-validation technique, is applied to the edge removed image. The despeckled image is finally synthesised using the extracted edge information to preserve the sharpness of edges and the texture. The proposed scheme outperforms many of the traditional despeckling schemes such as the Lee filter and the wavelet and bandlet based edge detection methods in terms of numeric and perceptual quality.

关键词： Synthetic aperture radar Lee filter Edge of a figure or solid Edge detection wavelets boundary detection algorithm Radar polarimetry Image wavelet transforms Rescue Specific absorption rate

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Supervised Semantic Gradient Extraction Using Linear-Time Optimization

Supervised Semantic Gradient Extraction Using Linear-Time Op...

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Shulin (Lynn) Yang Jue Wang Linda Shapiro University of Washington Adobe Research

ISBN: (纸本)9781467364102

This paper proposes a new supervised semantic edge and gradient extraction approach, which allows the user to roughly scribble over the desired region to extract semantically-dominant and coherent edges in it. Our approach first extracts low-level edgelets (small edge clusters) from the input image as primitives and build a graph upon them, by jointly considering both the geometric and appearance compatibility of edgelets. Given the characteristics of the graph, it cannot be effectively optimized by commonly-used energy minimization tools such as graph cuts. We thus propose an efficient linear algorithm for precise graph optimization, by taking advantage of the special structure of the graph. Objective evaluations show that the proposed method significantly outperforms previous semantic edge detection algorithms. Finally, we demonstrate the effectiveness of the system in various image editing tasks.

关键词： Line graph Semantics boundary detection algorithm Special structures Image Editing

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Design of Relative Motion and Attitude Profiles for Three-Dimensional Resident Space Object Imaging with a Laser Rangefinder

Design of Relative Motion and Attitude Profiles for Three-Di...

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IEEE Aerospace Conference

作者： Michael Nayak Jaclyn Beck Bogdan Udrea Space Development & Test Directorate NASA Goddard Space Flight Center Embry-Riddle Aeronautical Univ.

ISBN: (纸本)9781467318129

This paper focuses on the aerospace application of a single beam laser rangefinder (LRF) for 3D imaging, shape detection, and reconstruction in the context of a space-based space situational awareness (SSA) mission scenario. The primary limitation to 3D imaging from LRF point clouds is the one-dimensional nature of the single beam measurements. A method that combines relative orbital motion and scanning attitude motion to generate point clouds has been developed and the design and characterization of multiple relative motion and attitude maneuver profiles are presented. The target resident space object (RSO) has the shape of a generic telecommunications satellite. The shape and attitude of the RSO are unknown to the chaser satellite however, it is assumed that the RSO is un-cooperative and has fixed inertial pointing. All sensors in the metrology chain are assumed ideal. A previous study by the authors used pure Keplerian motion to perform a similar 3D imaging mission at an asteroid. A new baseline for proximity operations maneuvers for LRF scanning, based on a waypoint adaptation of the Hill-Clohessy-Wiltshire (HCW) equations is examined. Propellant expenditure for each waypoint profile is discussed and combinations of relative motion and attitude maneuvers that minimize the propellant used to achieve a minimum required point cloud density are studied. Both LRF strike-point coverage and point cloud density are maximized;the capability for 3D shape registration and reconstruction from point clouds generated with a single beam LRF without catalog comparison is proven. Next, a method of using edge detection algorithms to process a point cloud into a 3D modeled image containing reconstructed shapes is presented. Weighted accuracy of edge reconstruction with respect to the true model is used to calculate a qualitative "metric" that evaluates effectiveness of coverage. Both edge recognition algorithms and the metric are independent of point cloud density, therefore they

关键词： relative motion Clouds space targets Attitude laser range finders single beams flavour model PROPELLING CHARGES boundary detection algorithm Aerospace applications Three dimensional imaging

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BILATERAL EDGE DETECTORS

BILATERAL EDGE DETECTORS

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Abin Jose Chandra Sekhar Seelamantula Department of Electrical Engineering Indian Institute of Science

ISBN: (纸本)9781479903573

We propose to employ bilateral filters to solve the problem of edge detection. The proposed methodology presents an efficient and noise robust method for detecting edges. Classical bilateral filters smooth images without distorting edges. In this paper, we modify the bilateral filter to perform edge detection, which is the opposite of bilateral smoothing. The Gaussian domain kernel of the bilateral filter is replaced with an edge detection mask, and Gaussian range kernel is replaced with an inverted Gaussian kernel. The modified range kernel serves to emphasize dissimilar regions. The resulting approach effectively adapts the detection mask according as the pixel intensity differences. The results of the proposed algorithm are compared with those of standard edge detection masks. Comparisons of the bilateral edge detector with Canny edge detection algorithm, both after non-maximal suppression, are also provided. The results of our technique are observed to be better and noise-robust than those offered by methods employing masks alone, and are also comparable to the results from Canny edge detector, outperforming it in certain cases.

关键词： Bilateral filters Edge detection Domain kernel Range kernel Edge detection masks Edge detection boundary detection algorithm Masks bilateral filters Noise robustness Seeds detector telecommunication standards cellular radio Gauss edges

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Bionic vision-based synthetic aperture radar image edge detection method in non-subsampled contourlet transform domain

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IET RADAR SONAR AND NAVIGATION 2012年第6期6卷 526-535页

作者： Li, Q. -W. Huo, G. -Y. Li, H. Ma, G. -C. Shi, A. -Y. Hohai Univ Coll Comp & Informat Changzhou 213022 Peoples R China Beijing Jiaotong Univ Sch Comp & Informat Technol Beijing 100044 Peoples R China

For synthetic aperture radar (SAR) images, traditional edge detection methods can hardly extract the complete and true edges since they are sensitive to noise. In this study, the authors propose an edge detection method based on bionic vision in non-subsampled contourlet transform (NSCT) domain for SAR images, which makes use of the characteristics of NSCT (e.g. multiscale, multidirection edge expression and outstanding edge location) and the mechanisms of strengthening and positioning the image edge by fixational eye movements. First, source images are decomposed in the NSCT domain. The minimum mean squared error (MMSE) filter in the NSCT domain is adopted to reduce speckle noise of SAR images. Movement, difference and competition are applied on each subband to obtain original multiscale and multidirection subband edges. Lipschitz regularity and non-maximum suppression are also adopted to effectively remove noise points. Finally, hysteresis thresholding with adaptive thresholds is introduced to avoid streaking and trial-and-error, and multiscale edge fusion is used to reduce the false alarm rate. Edge extraction results of simulated and real SAR images demonstrate that the proposed method is better than other edge detection methods based on Canny operator, ratio of averages (ROA) operator, ratio of exponentially weighted averages (ROEWA) operator, wavelet modulus maximum and curvelet.

关键词： adaptive thresholding bionics subband Specific absorption rate Rescue Edge detection source image Domain Mean square error Radar polarimetry speckle noise boundary detection algorithm profile transformation edge image

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Edge detection for Facial Images under Noisy Conditions

Edge Detection for Facial Images under Noisy Conditions

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21st International Conference on Pattern Recognition (ICPR)

作者： Madabusi, Sudarshan Gangashetty, Suryakanth V. Int Inst Informat Technol Hyderabad 500032 Andhra Pradesh India

ISBN: (纸本)9784990644109;9781467322164

Edge detection is an important image processing technique used in face recognition. In this paper we propose an edge detection algorithm suitable for extracting edge maps from facial images under noisy conditions. We employ several improvised techniques like composite gradient variation measures, weighted wide convolution kernels and dual maxima detection. This helps in removing spurious edge points along stronger edges, extracting fine edge lines along facial boundaries and curvatures and suppressing noise. This is demonstrated by extracting edges from facial images degraded by Gaussian, speckle and salt and pepper noise. For performance measurement and evaluation Pratt's Figure of Merit and Signal to Noise statistics is used.

关键词： Mug shots Noise Edge detection Edge lines boundary detection algorithm salt-and-pepper noise Performance metrics Facial Recognition

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Target contour extraction for ship borne active range-gated imaging

Target contour extraction for ship borne active range-gated ...

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Conference on Optoelectronic Imaging and Multimedia Technology II

作者： Liu Chao Cao Yinan Wang Xinwei Zhou Yan Liu Yuliang Chinese Acad Sci Inst Semicond Lab Optoelect Syst Beijing 100083 Peoples R China

ISBN: (纸本)9780819493132

Target acquisition is of great importance for ship borne range-gated night vision system which can achieve target finding, target tracing and ranging. A digital image processing algorithm is developed for the mentioned night vision equipment above. Target contour is extracted using Canny edge detection algorithm based on self-adapted Otsu threshold segmentation. Furthermore, edge thinning, edge connection and morphologic methods are implemented to ameliorate the acquired contour. Pixels inside the contour are collected utilizing horizontal-vertical traverse. After ship targets from range-gated equipment being all tested, target contour and inner pixels can both be acquired through this algorithm.

关键词： boundary detection algorithm Ships contour Night vision goggles TARGET ACQUISITION Targets Edge detection edge thinning pixel

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