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检索条件"主题词=Change Detection Algorithms"

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An inverse voting algorithm for Hough Transform

An inverse voting algorithm for Hough Transform

引用

IEEE International Conference on Image Processing

作者： Dingding Chang S. Hashimoto School of Science and Engineering Waseda University Tokyo Japan

In this paper, we propose a new method for curve detection based on the inverse Hough Transform. The key idea of this method is to make the voting process on the image space instead of that on the parameter space in the conventional method, then convert the local peak detection problem in the parameter space into a parameter optimization problem. This leads to substantial savings, not only in storage requirements but also in the amount of calculation required. The experimental results and qualitative analysis showed that in comparison with the conventional Hough Transform methods, the new method has advantages of high speed, small storage arbitrary parameter range and high parameter resolution.< >

关键词： Voting Shape Optimization methods Image processing change detection algorithms Transforms Equations

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A new approach to corner extraction and matching for automated image registration

A new approach to corner extraction and matching for automat...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： S. Alkaabi F. Deravi Research and Development Center UAE Armed Forces Abu Dhabi U.A.E. Department of Electronics University of Kent Canterbury UK

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Ensemble based incremental SVM classifiers for changing environments

Ensemble based incremental SVM classifiers for changing envi...

引用

International International Symposium on Computer and Information Sciences (ISCIS)

作者： Aycan Yalcin Zeki Erdem Fikret Gurgen Computer Engineering Department Bebek Bogazici University Istanbul Turkey TUBITAK Marmara Research Center Information Technologies Institute Gebze Kocaeli Turkey

For most of the real-world applications, two main challenges are infinite data flow and time changing concepts. Generally data are gathered over a long period of time and the data generation mechanism may change with time. In a dynamic environment, knowledge about the environment is rarely complete due to time-changing concepts. In recent years, a lot of methods have been proposed for effective learning in changing environments. Due to their ability to learn from new data, incremental learning algorithms can be used for learning in changing environments. In this paper we propose an ensemble based incremental learning approach with SVM (support vector machines) classifiers to provide ability to learn new domain knowledge in a non-stationary environment. Experiments on different datasets with simulated concept drift show promising results.

关键词： Support vector machines Support vector machine classification Training data change detection algorithms Voting Iterative algorithms Data flow computing Data engineering Information technology Application software

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Binary fuzzy rough set model based on triangle modulus and its application to image processing

Binary fuzzy rough set model based on triangle modulus and i...

引用

IEEE International Conference on Cognitive Informatics

作者： Dan Wang Meng-da Wu Dept. of Mathematic and System Science National University of Defense Technology Changsha 410073 China Dept. of Mathematic and System Science National University of Defense Technology Changsha China

Rough sets theory is an important tool that process uncertainty information. In this paper, image processing based on rough sets theory is discussed in detail. The paper presents a binary fuzzy rough set model based on triangle modulus, which describes binary relationship by upper approximation and lower approximation. As image can be described by binary relationship, the upper approximation and lower approximation can be used to represent an image. The model in this paper is well fit for processing image that have gentle gray change. An edge detection algorithm by the upper approximation and the lower approximation of image is presented, and image denoising also is discussed. At last, its better effect can be testified by many experiments.

关键词： Fuzzy sets Image processing Rough sets Image edge detection Uncertainty change detection algorithms Pattern analysis Fuzzy set theory Approximation algorithms Image denoising

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A warning algorithm for Lane Departure Warning system

A warning algorithm for Lane Departure Warning system

引用

IEEE Symposium on Intelligent Vehicle

作者： Xun Dai Anton Kummert Su Birm Park Diane Neisius University of Wuppertal Communication Theory Wuppertal Germany Delphi Electronics and Safety Wuppertal Germany

ISBN: (纸本)9781424435036

Single vehicle road departure (SVRD) is a main cause of enormous loss of life and property on highways. In total, SVRD accidents amount to around 20 percent of traffic accidents and 40 percent of fatalities in total. Recent developments of advanced driver assistant system (ADAS) such as lane departure warning (LDW) system which perceives road boundaries through optical sensors that trigger a warning when the driver leaves the lane without using their turn signal. However, a robust LDW system can not be realized with only turn signal usage to suppress warnings during an intended lane change. This paper will analyze not only driving position, but also driving tendency and driver state to determine whether an unintended lane departure is detected. The paper will explore how the warning algorithm summarizes information from the environment, vehicle and driver and establishes a model so that real unintended lane departure can be detected and a warning will be triggered accordingly.

关键词： Alarm systems Road accidents Road vehicles Optical losses Road transportation Optical sensors Robustness change detection algorithms Vehicle driving Vehicle detection

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Efficient Application of AI for Target Tracking and Monitoring in Airborne Images:

Efficient Application of AI for Target Tracking and Monitori...

引用

Remote Sensing Symposium (InGARSS), 2020 IEEE India Geoscience and

作者： Vatsala Singh K.P. Singh Mody University of Science and Technology Rajasthan India Indian Institute of Technology Banaras Hindu University Varanasi India

ISBN: (纸本)9781665442503

With evolution of computing technology, its capability of solving complex problems faced in real life scenario have certainly escalated. One such problem of extraction and counting of building footprints using aerial images obtained from drone is looked upon in this paper.A typical image obtained from drone has many characteristic features like the spatial resolution i.e. the area that a single pixel of the image covers, pixel resolution and many more, and provides users with a 3 channel(RGB) image of a certain region which helps in assessing the landscape distribution, vegetation cover urbanization and monitoring the area. With so many efficient and intriguing applications, drone images have seen a definite upsurge in recent years. However, all such applications are painstakingly tedious and certainly require automation. Researchers are constantly working towards solving this problem and providing an optimal solution economically and computationally *** paper proposes to solve this problem by carrying out basic image processing steps enhanced using Deep Learning by efficiently harnessing the statistical features of image and applying adaptive thresholding to semantically segment and count building footprints, thus deriving a holistic algorithm that is capable of handling image with different spatial or pixel resolution.

关键词： Thresholding (Imaging) Target tracking change detection algorithms Buildings Vegetation mapping Prediction algorithms Feature extraction

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Analysis of Streaming Clustering Using an Incremental Validity Index

Analysis of Streaming Clustering Using an Incremental Validi...

引用

IEEE International Conference on Fuzzy Systems

作者： Omar A. Ibrahim James M. Keller James C. Bezdek Dept of Electrical Engineering and Computer Science Columbia Mo USA

In this paper, we study the internal incremental Davies-Bouldin (iiDB) cluster validity index in the context of streaming data analysis. We extend the original index to a more general version parameterized by the exponent of membership weights. Then we illustrate how the iiDB can be used to analyze and understand the performance of the Extended Robust Online Streaming Clustering (EROLSC) algorithm. We give examples that illustrate the appearance of a new cluster, the effect of different cluster sizes, handling of outlier data samples, and the effect of the input order on the resultant cluster history.

关键词： Clustering algorithms Indexes Partitioning algorithms Microsoft Windows change detection algorithms Electrical engineering Covariance matrices

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Hardware oriented rate control algorithm and implementation for realtime video coding

Hardware oriented rate control algorithm and implementation ...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Hung-Chi Fang Tu-Chih Wang Yu-Wei Chang Liang-Gee Chen Department of Electrical Engineering National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University

ISBN: (纸本)0780379659

In this paper, a novel rate control algorithm suitable for realtime video encoding is proposed. The proposed algorithm uses mean absolute error (MAE) results of motion estimation (ME) to achieve bitrate control. Neither pre-analysis nor multi-pass encoding is required in our algorithm, which makes realtime hardware implementation possible. A new hardware oriented scene change detection method is also included in this rate control framework to achieve better video quality. Experiment shows our rate control algorithm behaves well in all situations. Hardware architecture for this algorithm is also described. Implementation shows our proposed algorithm can be efficiently integrated into low cost, high efficiency video encoder.

关键词： Hardware Video coding change detection algorithms Encoding Error correction Motion estimation Bit rate Motion control Layout Costs

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Building wide area 2-D site models from high resolution fully polarimetric synthetic aperture radar images

Building wide area 2-D site models from high resolution full...

引用

International Symposium on Computer Vision (ISCV)

作者： S. Kuttikkad R. Chellappa Department of Electrical Engineering and Center for Automation Research University of Maryland College Park MD USA

Wide area site models are useful for delineating regions of interest and assisting in tasks like monitoring and change detection. They are also useful in registering a newly acquired image to an existing one of the same site, or to a map. This paper presents a complete algorithm for building an approximate 2-D wide-area site model from high resolution, polarimetric Synthetic Aperture Radar (SAR) data. A three stage algorithm-involving detection of possible targets, statistical segmentation of the data into homogeneous regions, and validation of segmentation results-is used for this task. Constant False Alarm Rate (CFAR) detectors are used for target detection, while maximum likelihood labeling is used for initial segmentation. Knowledge of the sensor heading and other geometric cues are used to refine the initial segmentation and to extract man-made objects like buildings, and their shadows, as well as roads, from these images.

关键词： Radar detection Image segmentation change detection algorithms Maximum likelihood detection Monitoring Polarimetric synthetic aperture radar Synthetic aperture radar Detectors Object detection Labeling

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Geometric image masking for segmenting dynamic projected imagery

Geometric image masking for segmenting dynamic projected ima...

引用

IEEE International Conference on Image Processing

作者： G. Pingali A. Hampapur IBM Thomas J. Watson Research Center Hawthorne NY USA

Projected interfaces are gaining popularity as a means of access to information anywhere in a space without the need for special devices or monitors. In this context, it is of particular interest to automatically steer the projected interface to appropriate surfaces based on the location of the user in the space. This requires the users be tracked precisely, and in real time, as they move about in the environment, in spite of continuously varying and moving projected imagery in the background. This is challenging as the projection regions also appear as foreground. This paper presents a geometric image masking technique that separately segments out regions corresponding to the user and projected imagery in multiple camera views, and enables precise three-dimensional tracking of the user.

关键词： Image segmentation Cameras Layout Equations Mirrors change detection algorithms Legged locomotion TV Costs

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