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检索条件"主题词=Detection algorithms"

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Image Defect detection Methods for Visual Inspection Systems

Image Defect Detection Methods for Visual Inspection Systems

引用

International Conference on CAD Systems in Microelectronics (CADSM)

作者： L. Tomczak V. Mosorov D. Sankowski J. Nowakowski Computer Engineering Department Technical University of Lodz Poland Computer Engineering Department Technical University of Lodz Poland

Two texture defect detection methods for automatic visual inspection systems will be presented in this paper. They divide up an analysed texture image into non-overlapping samples, and then calculate features of each sample using statistical analysis. Finally, the clustering of those features is applied to recognize the sample as defective or non-defective. Unlike the well-known methods, the proposed schemes do not require a previous training step to collect defective and non- defective texture samples. The experimental results show that these methods are effective and more accurate than earlier methods for image texture defect detection.

关键词： Inspection Principal component analysis Matrix decomposition Image texture analysis Singular value decomposition Image analysis Humans detection algorithms Algorithm design and analysis Eigenvalues and eigenfunctions

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A change-detection algorithm based on structure and colour

A change-detection algorithm based on structure and colour

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： L. Di Stefano S. Mattoccia M. Mola Advanced Research Center on Electronic Systems University of Bologna Bologna Italy

The paper proposes a novel change-detection algorithm for automated video surveillance applications. The algorithm is based on the idea of incorporating into the background model a set of simple low-level features capable of capturing effectively "structural" (i.e. robust with respect to illumination variations) information. Thanks to this approach, and unlike most conventional change-detection algorithms, the proposed algorithm is capable of handling correctly still and slow objects as well as of working properly throughout very long time spans. Moreover, the algorithm can naturally interact with the higher-level processing modules found in advanced video-based surveillance systems in order to allow for flexible and intelligent background maintenance.

关键词： Change detection algorithms Layout Lighting Robustness Surveillance Image analysis Cameras Image color analysis detection algorithms Pixel

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Design of an automatic step intention detection system for a hybrid gait orthosis

Design of an automatic step intention detection system for a...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： P. Jaspers W. Van Petegem G. Van der Perre L. Peeraer Division of Biomechanics and Engineering Design Katholieke Universiteit Leuven Heverlee Belgium Centre for Evaluation and Rehabilitation of Motor Functions University Hospital Pellenberg Pellenberg Belgium

An algorithm is presented to detect the step intention of paraplegics walking with a hybrid gait orthosis, the Advanced Reciprocating Gait Orthosis (ARGO) in combination with Functional Electrical Stimulation (FES). It is based on the information of four pressure sensors mounted under the feet. A finite state approach is used. The system has been tested by two paraplegics with positive results.

关键词： Sensor systems Sensor phenomena and characterization Foot detection algorithms Neuromuscular stimulation Control systems Biological system modeling Biomechanics Design engineering Algorithm design and analysis

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Research Outlier detection Technique Based on Clustering Algorithm

Research Outlier Detection Technique Based on Clustering Alg...

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Conference on Control and Automation (CA)

作者： Huang Tao Tan Yanna Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781479982073

In this paper, in clustering and outlier detection as a starting point, it put forward a kind of DBSCAN-LOF algorithm, to the core definition of object DBSCAN, then the LOF only need to operate on noncore object, thereby reducing the number of the original LOF algorithm for global object operation, the results show that the algorithm improve the running efficiency of the LOF, and the clustering effect of DBSCAN, and the at the same time, the clustering and outlier detection results is produced.

关键词： Clustering algorithms Algorithm design and analysis Data mining Knowledge discovery detection algorithms Sorting Software algorithms

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Eye detection based on rank order filter and projection function

Eye detection based on rank order filter and projection func...

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International Conference on Computer Design and Applications (ICCDA)

作者： Ling Gan Qingjun Liu College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9781424471645;9781424471638

Eye detection is the preconditions for fatigue driving detection. In this paper, considering the deficiency of the origin algorithm based on rank order filter, an improved eye detection algorithm based on rank order filter and projection function is proposed. At first, according to the structure features and gray features, an ellipse mask combined with rank order filter is used to find the eye candidates initially. Then projection function is applied to excluding the no eye candidates and exactly locating eyes. By the comparative experiment of eye detection in the BioID face database, the results have shown the higher accuracy and efficiency of the improved algorithm.

关键词： Filters Eyes Fatigue detection algorithms Face detection Educational institutions Computer science Road accidents Telecommunication computing Gallium nitride

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A system for reliable dissolve detection in videos

A system for reliable dissolve detection in videos

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IEEE International Conference on Image Processing

作者： R. Lienhart A. Zaccarin Microprocessor Research Labs Intel Corporation Santa Clara CA USA

Automatic shot boundary detection has been an active research area for nearly a decade and has led to high performance detection algorithms for hard cuts, fades and wipes. Reliable dissolve detection, however, is still an unsolved problem. We present the first robust and reliable dissolve detection system. A detection rate of 75% was achieved while reducing the false alarm rate to an acceptable level of 16% on a test video set for which so far the best reported detection and false alarm rate had been 66% and 59%, respectively. In addition, a dissolve's temporal extent is estimated, too. The core ideas of our novel approach are firstly the creation of a dissolve synthesizer capable of creating in principle an infinite number of dissolve examples of any duration from a video database of raw video footage allowing us to use an advanced machine learning algorithm such as neural networks and support vector machines which require large training sets, secondly, two simple features capturing the characteristics of dissolves, thirdly, a fully temporal multi-resolution search based on a fixed position and fixed-scale transition/special effect detector enabling us to determine also the true duration of detected dissolves, and finally, a post processing step which uses global motion estimation to further reduce the number of falsely detected dissolves.

关键词： Videos Motion detection Gunshot detection systems detection algorithms Robustness Testing Synthesizers Spatial databases Machine learning algorithms Neural networks

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Quality assessment of the fire hazard forecast based on a fire potential index for the Mediterranean area by using a MSG/SEVIRI based fire detection system

Quality assessment of the fire hazard forecast based on a fi...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： G. Laneve E. G. Cadau Centro di Ricerca Progetto San Marco University of Roma La Sapienza Rome Italy

This paper is devoted to describe the activity carried out by CRPSM(Centro di Ricerca Progetto San Marco) in the framework of the SIGRI(Italian acronym for Integrated System for Fire Risks Management) project. This project aims to develop a system, based on satellite data, able to support operationally the activities of users like Italian Civil Protection Agencies or Fire Dept. involved in fighting wild fires. In particular, the system should be able to support all the phases in which a fire fighting activity can be distinguished, namely: Territory management and resources dislocation (fire risk indices), fires detection and monitoring, damage assessment (burned areas and emissions in atmosphere). This paper presents the results obtained in the process of assessing the quality of a fire hazard forecast based on a fire potential index especially designed for the Mediterranean areas. This quality assessment is carried out comparing the daily computed indices with the fire distribution obtained by using a fire detection algorithm based on SEVIRI/MSG *** fact, using a fire detection algorithm (SFIDE, System for Fires detection), recently proposed by the authors, a despite of its low spatial resolution,the SEVIRI system is able to reveal, at latitudes corresponding to Italy,fires covering an area of the order of 0.1 ha. The fire potential index (FPI) is one of the most suitable to be computed by using satellite data even if ancillary information are still needed. The computation of this index requires the estimate of the relative greenness, the evaluation of the leaves humidity, the preparation of vegetation fuel maps. Among the parameters needed to compile this index the fuel type map is particularly crucial. In fact, accurate maps of this kind are not available for the Italian territory. Then, first of all, using Corine Land Cover and other available vegetation maps, medium resolution satellite images and "in situ" observations CRPSM carried out the development o

关键词： Fires Quality assessment Hazards Satellites Risk management detection algorithms Image resolution Vegetation mapping Fuels Protection

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A novel approach to change detection based on a coarse-to-fine strategy

A novel approach to change detection based on a coarse-to-fi...

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IEEE International Conference on Image Processing

作者： A. Bevilacqua L. Di Stefano A. Lanza G. Capelli Department of Electronics Computer Science and Systems (DEIS) Advanced Research Centre .Ercole De Castro. (ARCES) University of Bologna Bologna Italy

We present a novel approach to the change detection problem based on a coarse-to-fine strategy. The basic idea consists in assigning to an efficient preliminary coarse-level detection the task to filter out the well known possible false changes (e.g., those due to camera noise and small displacements, or to scene illumination changes). This provides the subsequent fine-level detection with reliable supermasks of the true changed areas in the scene. In this way, the fine-level detection can "focus the attention" on limited parts of the frames, thus yielding remarkable advantages in terms of computational efficiency. Here, just a coarse-level detection algorithm based on background subtraction and on the concept of structure is presented, to stress that any pixel-level algorithm can be used afterwards and benefit in terms of robustness as well as of computational efficiency.

关键词： Cameras Layout Lighting detection algorithms Change detection algorithms Event detection Noise robustness Computer science Stress Computer vision

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Skin detection using color processing mechanism inspired by the visual system

Skin detection using color processing mechanism inspired by ...

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IET Conference on Image Processing (IPR 2012)

作者： Qing Xiang Wu Rongtai Cai Lijuan Fan Chengmei Ruan Gang Leng School of Physics and OptoElectronic Technology Fujian Normal University Fujian Fuzhou 350007 China Intelligent Systems Research Centre School of Computing & Intelligent Systems University of Ulster at Magee Londonderry Northern Ireland BT48 7JL UK

ISBN: (纸本)9781622762675

Skin detection is an important procedure for face detection, hand gesture analysis, and objectionable image filtering. In this paper, a skin detection algorithm is proposed according to the colour processing mechanism inspired by the visual system. In the algorithm different types of neurons are used to deal with skin colour and texture. Inspired by receptive fields of rod, cone and orientation selectivity neurons in the visual system, a neural network is proposed to identify skin area in an image. The network contains three types of cones, one type of rod and four types of orientation neurons. Three cones are in response to red, green and blue lights respectively. The rods are in response to brightness. Orientation neurons are used to detect textures of skin. Through their specific receptive fields, the network can be trained to identify skin areas. The experimental results show that the proposed algorithm is comparable to current skin segmentation algorithms.

关键词： Neural networks Skin detection Colour image segmentation Visual system skin epidermis (animal) Visual System Receptive field image filtering detection algorithms Neurons rod textures COLOR PROCESSING Vertebrate Photoreceptor Cells Cerebellar Herniation

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Fast and reliable obstacle detection and segmentation for cross-country navigation

Fast and reliable obstacle detection and segmentation for cr...

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IEEE Symposium on Intelligent Vehicle

作者： A. Talukder R. Manduchi A. Rankin L. Matthies Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA University of California Santa Cruz CA USA

Obstacle detection (OD) is one of the main components of the control system of autonomous vehicles. In the case of indoor/urban navigation, obstacles are typically defined as surface points that are higher than the ground plane, but in cross-country and unstructured environments the notion of "ground plane" is often not meaningful. We introduce a fast, fully 3D OD technique that overcomes such a problem, reducing the risk of false-negatives while keeping the same rate of false-positives. A simple addition to our algorithm allows one to segment obstacle points into clusters, where each cluster identifies an isolated obstacle in 3D space. Obstacle segmentation corresponds to finding the connected components of a suitable graph, an operation that can be performed at a minimal additional cost during the computation of obstacle points. Rule-based classification using 3D geometrical measures derived for each segmented obstacle is then used to reject false-obstacles (for example, objects that are small in volume, or of low height). Results for a number of scenes of natural terrain are presented, and compared with a pre-existing obstacle detection algorithm.

关键词： Navigation Vehicle detection Control systems Remotely operated vehicles Mobile robots Clustering algorithms Computational efficiency Volume measurement Layout detection algorithms

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