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检索条件"主题词=Detection Algorithms"

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An adaptive Shot Change detection algorithm using an average of absolute difference histogram within extension sliding window

An adaptive Shot Change Detection algorithm using an average...

引用

IEEE International Symposium on Consumer Electronics (ISCE)

作者： Won-Hee Kim Jong-Nam Kim Department of Computer Engineering Pukyong National University Busan South Korea

Shot change detection is a main technique for automatic temporal segmentation of video, which requires adaptive adjustment of thresholds. In this paper, we propose an adaptive shot change detection algorithm using histograms of frames within extension sliding window. The proposed method generates an adaptive threshold which is calculated by an average of absolute difference histogram within extension sliding window. We obtained better the detection rate than conventional methods maximally 10% in F1. The proposed method will be helpful in searching video data on various applications.

关键词： detection algorithms Histograms Gunshot detection systems Cameras Change detection algorithms Data mining Detectors Transform coding Image coding Video sequences

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The Performance Merit of Dynamic Threshold Energy detection Algorithm in Cognitive Radio Systems

The Performance Merit of Dynamic Threshold Energy Detection ...

引用

International Conference on Information Science and Engineering (ICISE)

作者： Jinbo Wu Guicai Yu Tao Luo Guangxin Yue School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781424449095

In cognitive radio systems, secondary users should determine correctly whether the primary user is absent or not in a certain spectrum within a short detection period. Traditional spectrum sensing schemes based on fixed threshold are sensitive to noise uncertainty, a fractional fluctuate of average noise power in a short time will lead to the accuracy of spectrum detection decreasing seriously. In this paper we propose a novel dynamic threshold energy detection algorithm in cognitive radio systems. Theoretical analysis and simulation results show that the proposed strategy can combat the noise uncertainty effectively, and good detection accuracy can be attained, if a suitable detection threshold is chosen. That is, the proposed scheme can enhance the robustness of combating the noise uncertainty and veracities of the spectrum sensing.

关键词： detection algorithms Cognitive radio Additive white noise Gaussian noise Uncertainty Detectors 1f noise Signal detection Power engineering and energy AWGN

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Breast border extraction and pectoral muscle detection using wavelet decomposition

Breast border extraction and pectoral muscle detection using...

引用

Eurocon

作者： Mario Mustra Jelena Bozek Mislav Grgic Faculty of Electrical Engineering and Computing Department of Wireless Communication University of Zagreb Zagreb Croatia

Digital mammography is used more and more each day in comparison with screen film mammography (SFM). Main advantage of digital mammography for image processing is the use of images with few or no artifacts that can occur on SFM images. Finding breast border contour is therefore easier and gives more precise results. On the other hand, detection of pectoral muscle and breast abnormalities has almost the same results in both cases. The presence of pectoral muscle can affect results of lesion detection algorithms so it is recommended to have it removed from the image. detection and segmentation of pectoral muscle can also help in image registration for further analysis of breast abnormalities such as bilateral asymmetry. Algorithm presented in this paper uses hybrid method for the pectoral muscle detection. Proposed method uses bit depth reduction and wavelet decomposition for finding pectoral muscle border. Algorithm has been tested on the set of 40 digital mammography images.

关键词： Breast Muscles Mammography Image processing Lesions detection algorithms Image segmentation Image registration Image analysis Testing

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A novel template matching method for human detection

A novel template matching method for human detection

引用

IEEE International Conference on Image Processing

作者： Nguyen Duc Thanh Wanqing Li Philip Ogunbona Advanced Multimedia Research Laboratory ICT Research Institute University of Wollongong Australia

This paper proposes a novel weighted template matching method. It employs a generalized distance transform (GDT) and an orientation map (OM). The GDT allows us to weight the distance transform more on the strong edge points and the OM provides supplementary local orientation information for matching. Based on the matching method, a two-stage human detection method consisting of template matching and Bayesian verification is developed. Experimental results have shown that the proposed method can effectively reduce the false positive and false negative detection rates and perform superiorly in comparison to the conventional Chamfer matching method.

关键词： Humans Shape Gas discharge devices detection algorithms Bayesian methods Leg Motion detection Motion analysis Tree data structures Biological system modeling

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Saliency-based automatic target detection in forward looking infrared images

Saliency-based automatic target detection in forward looking...

引用

IEEE International Conference on Image Processing

作者： Wei Li Chunhong Pan Li-xiong Liu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China School of Computer Science and Technology Beijing Institute of Technology China

A saliency-based target detection method for forward looking infrared (FLIR) image is proposed. Firstly, saliency map is computed using scale-space representation and separated into dark saliency map (DSM) and bright saliency map (BSM). Secondly, dark and bright regions of interest (ROI) are detected by respective type of saliency map using marker-based maximally stable extremal regions (MSER) detection algorithm. Finally, shape matching algorithm is applied after grouping of the two types of ROI for object detection. Experimental results show that this work provides a promising way to solve the problems caused by salient dark parts of target.

关键词： Object detection Infrared imaging Infrared detectors Shape detection algorithms Signal processing algorithms Laboratories Pattern recognition Automation Computer science

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detection of Rock Fractures Junction in Gray-Level Images

Detection of Rock Fractures Junction in Gray-Level Images

引用

Congress on Image and Signal Processing, CISP

作者： Minghao Liu W. B. Jin W. X. Wang Sino-Korea Chongqing GIS Research Center College of Computer Science Chongqing University of Posts and Telecommunications Chongqing China Institute of Image Processing College of Computer Science Chongqing University of Posts and Telecommunications Chongqing China

Rock fractures junctions are important objects for detection of rock fracture. Traditionally, junction detectors are devoted to the step-edge corners. Such corners are usually located using a Laplascian operator (zero-crossings or extrema) or a curvature measure based on the gradient direction. However, the gradient direction of a line does not exist, and a line junction does not correspond to a zero-crossing of the Laplacian. Consequently, step-edge corner detectors are not suitable for line junctions. Their response to a single line junction is not unique. There are other methods to detect the junction. Most of them find L-shaped corners, but create multiple or no responses for more complex junctions. This paper proposes a robust detection method for gray-level line junction which is called the neighborhood pixel-track algorithm. Examples are provided based on experiments with synthetic and real images. The achieved results demonstrate that such junction detection algorithm can successfully identify T-and Y-junctions, and of degree four X-junctions or more complex intercross of rock fractures.

关键词： Detectors Educational institutions Computer science Atmospheric measurements Geologic measurements Pollution measurement detection algorithms Radioactive pollution Earth Image edge detection

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A Gaussian mixture model based statistical classification system for neonatal seizure detection

A Gaussian mixture model based statistical classification sy...

引用

IEEE Workshop on Machine Learning for Signal Processing

作者： Eoin M. Thomas Andriy Temko Gordon Lightbody William P. Marnane Geraldine B. Boylan Dept. of Electrical Engineering UCC Cork Ireland Department of Paediatrics and Child Health Cork University of Hospital Cork Ireland Dept. of Paediatrics and Child Health Cork University Hospital Cork Ireland

A neonatal seizure detection system is proposed based on a Gaussian mixture model classifier. Linear discriminant analysis and principal component analysis are compared for the task of feature vector preprocessing. A postprocessing scheme is developed from the probability of seizure estimate in order to improve the performance of the system. Results are reported on a dataset of 17 patients with a total duration of 267.9 hours, the average ROC area of the system is 95.6%.

关键词： Pediatrics Electroencephalography Independent component analysis Artificial neural networks Linear discriminant analysis Principal component analysis detection algorithms Frequency Pattern recognition Support vector machines

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A sparsity detection framework for on-off random access channels

A sparsity detection framework for on-off random access chan...

引用

IEEE International Symposium on Information Theory

作者： Alyson K. Fletcher Sundeep Rangan Vivek K. Goyal University of California Berkeley USA Qualcomm Technologies USA Massachusetts Institute of Technology USA

This paper considers a simple on-off random multiple access channel (MAC), where n users communicate simultaneously to a single receiver. Each user is assigned a single codeword which it transmits with some probability lambda over m degrees of freedom. The receiver must detect which users transmitted. We show that detection for this random MAC is mathematically equivalent to a standard sparsity detection problem. Using new results in sparse estimation we are able to estimate the capacity of these channels and compare the achieved performance of various detection algorithms. The analysis provides insight into the roles of power control and multi-user detection.

关键词： Matching pursuit algorithms Multiuser detection Multiaccess communication Paper technology Channel capacity Power control Silicon carbide detection algorithms Wireless application protocol Access protocols

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Video shot boundary detection by dominant sets approach

Video shot boundary detection by dominant sets approach

引用

IEEE Signal Processing and Communications Applications (SIU)

作者： Emrah Asan A.Aydin Alatan Elektrik Elektronik Muhendisligi Bolumu O.D.T.U Turkiye

In this study, a video shot boundary detection algorithm based on the dominant sets concept is proposed. Dominant sets method is a graph theoretic clustering algorithm. Proposed method is based on a weighted undirected graph. Candidate shot boundaries are determined and graphs are constructed by taking 2 frames from the right of the candidate position and 4 frames from the left of the candidate position. Edge weights among the vertices are evaluated by using pairwise similarities of frames. By using the complete information of the graph, a set of the vertices mostly similar to each other and dissimilar to the others is detected. True cut positions are determined if the dominant set includes the 4 frames before the candidate position. The simulation results indicate that the proposed algorithm can be used for abrupt shot boundary detection.

关键词： Gunshot detection systems detection algorithms Clustering algorithms Internet Discrete cosine transforms

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2D staircase detection using real AdaBoost

2D staircase detection using real AdaBoost

引用

International Conference on Information, Communications and Signal Processing

作者： Sisong Wang Han Wang Autonomous Robotics Research Laboratory School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781424446568

This paper proposes a frontal staircase detection algorithm using both classical Haar-like features and a novel set of PCA-base Haar-like features. Real AdaBoost is used for training a cascaded classifier. The PCA-based Haar-like features are extremely efficient at rejecting background regions at early stages in the cascade. A specifically designed scanning scheme made the algorithm constantly time efficient to different image sizes. An multi-detections integration scheme that is exclusive for staircase detection is extremely useful at further rejecting false positives. A new evaluation metric is proposed to rate each final detection, instead of Boolean classifying it. Experimental results show that the approach can detect staircases accurately at extremely low false positive rate.

关键词： Object detection Paper technology Humans Face detection Detectors Robots Laboratories detection algorithms Algorithm design and analysis Navigation

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