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A New Vehicle Detection Approach in Traffic Jam Conditions

A New Vehicle Detection Approach in Traffic Jam Conditions

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Bing-Fei Wu Jhy-Hong Juang Ping-Tsung Tsai Ming-Wei Chang Chung-Jui Fan Shin-Ping Lin Jennifer Yuh-Jen Wu Hsia Lee Department of Electrical and Control Engineering National Chiao Tung University Hsinchu Taiwan

The well-known vehicle detectors utilize the background extraction methods to segment the moving objects. The background updating concept is applied to overcome the luminance variation which results in the error detection. These systems will meet a challenge when detecting the vehicles in the traffic jam conditions at sunset. The vehicles will cover the road surface so that the background information cannot be smoothly updated. Once the traffic is released, the existing background is not suitable for the moving segmentation. The main contribution of this paper is that an efficient vehicle detection approach is proposed to improve the detection accuracy in traffic jam conditions. The land mask decision gives the land information and the merged boundary box rule is presented to realize vehicle detection. The signed square normalized correlation coefficient calculation is addressed, and it is applied to vehicle tracking. The experimental results show that this approach works well in highway and urban area with high accuracy

关键词： Vehicle detection Object detection Road vehicles Infrared detectors Vehicle dynamics computational intelligence signal processing Control engineering Intelligent vehicles Automated highways

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Robotic Localization and Separation of Concurrent Sound Sources using Self-Splitting Competitive Learning

Robotic Localization and Separation of Concurrent Sound Sour...

引用

ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Fakheredine Keyrouz Werner Maier Klaus Diepold Technische Universitãt Miünchen Munich Germany

We combine binaural sound-source localization and separation techniques for an effective deployment in humanoid-like robotic hearing systems. Relying on the concept of binaural hearing, where the human auditory 3D percepts are predominantly formed on the basis of the sound-pressure signals at the two eardrums, our robotic 3D localization system uses only two microphones placed inside the ear canals of a robot head equipped with artificial ears and mounted on a torso. The proposed localization algorithm exploits all the binaural cues encapsulated within the so-called head related transfer functions (HRTFs). Taking advantage of the sparse representations of the ear input signals, the 3D positions of two concurrent sound sources is extracted. The location of the sources is extracted after identifying which HRTFs they have been filtered with using a well-known self-splitting competitive learning clustering algorithm. Once the location of the sources are identified, they are separated using a generic HRTF dataset. Simulation results demonstrated highly accurate 3D localization of the two concurrent sound sources, and a very high signal-to-interference ratio (SIR) for the separated sound signals

关键词： Auditory system Ear Humans Microphones signal processing algorithms Animals computational intelligence Humanoid robots Intelligent robots Head

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An Integrated Neuro-Fuzzy Approach to MPEG Video Transmission in Bluetooth

An Integrated Neuro-Fuzzy Approach to MPEG Video Transmissio...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： H. B. Kazemian S. Chantaraskul Computing Communications Technology and Mathematics Department London Metropolitan University London UK

This paper presents an integrated neuro-fuzzy (NF) scheme and a rule-based-fuzzy (RBF) scheme applications to Moving Picture Expert Group (MPEG) video transmission in Bluetooth. In a Bluetooth network, transmission rate is unpredictable due to interferences by other wireless devices or general Bluetooth channel noises. MPEG variable bit rate (VBR) video transmission is also unreliable and presents long delay and excessive data loss, due to variations in bit rate. It is therefore almost impossible to transmit MPEG VBR video over a Bluetooth channel, without data loss, excessive time delay or image quality degradation. In this work, a traffic-shaping buffer is introduced before the host controller interface (HCI) of the Bluetooth protocol stack. An integrated NF scheme reduces the burstiness of the traffic-shaper output rate to enable the MPEG VBR video to comply with the generic cell rate algorithm contract before entering the Bluetooth channel. The computer simulation results show that the application of the proposed scheme reduces excessive time delay and data loss at the HCI, as compared with a conventional video transmission in Bluetooth

关键词： Bluetooth Propagation losses Noise measurement Bit rate Delay effects Traffic control Human computer interaction MPEG standards Interference image quality

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Influence of signal Pre-processing in the Efficiency of Algorithms Based on Neural Networks for Disturbance Classification

Influence of Signal Pre-Processing in the Efficiency of Algo...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： M.F. de Medeiros C.K.S. Santos J.T. de Oliveira P.Sda.M. Pires J.D. de Melo A.D.D. Neto J.J.A.L. Leitao DCA UFRN Natal Brazil Universidade Federal do Rio Grande do Norte Natal RN BR

Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in power systems, looking for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances $providing an automatic assessment - techniques of digital signal processing can be helpful. The Wavelet Transform has become a very efficient tool for the analysis of voltage or current signals, obtained immediately after disturbances occurrences in the network. This paper presents a methodology based on the discrete wavelet transform to implement this process. It uses a comparison between distribution curves of signals energy, with and without disturbance. This is done for different resolution levels of its decomposition in order to obtain descriptors that permit its classification, using artificial neural networks

关键词： Neural networks Discrete wavelet transforms signal analysis Power system management signal processing algorithms Information analysis signal processing Power system analysis computing Energy management Digital signal processing

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Secure Authentication for Face Recognition

Secure Authentication for Face Recognition

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： M. A. Dabbah W. L. Woo S. S. Dlay University of Newcastle Newcastle-upon-Tyne UK

In this paper, we present a new technique to protect the face biometric during recognition, using the so called cancellable biometric. The technique is based on image-based (statistical) face recognition using the 2DPCA algorithm. The biometric data is transformed to its cancellable domain using polynomial functions and co-occurrence matrices. Original facial images are transformed non-linearly by a polynomial function whose parameters can be change accordingly to the issuing version of the secure cancellable template. Co-occurrence matrices are also used in the transform to generate a distinctive feature vector which is used for both security and recognition accuracy. The Hadamard product is used to construct the final cancellable template. It shows high flexibility in proving a new relationship between two independent covariance matrices, which is mathematically proven. The generated cancellable templates are used in the same fashion as the original facial images. The 2DPCA recognition algorithm has been used without any changes; the transformations are applied on the input images only and yet with higher recognition accuracy. Theoretical and experimental results have shown high irreversibility of data with improved accuracy of up to 3% from the original data

关键词： Authentication Face recognition Biometrics Protection image recognition Humans Filters signal processing algorithms Bioinformatics Polynomials

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Study of unsaturated magnetic image processing in wire rope aplication

Study of unsaturated magnetic image processing in wire rope ...

引用

作者： Tan, Xiaojiang Zhang, Juwei Henan University of Science and Technology College of Electrical Engineering Luoyang China

ISBN: (纸本)9781538636749

Traditional magnetic flux leakage signal need be processed through each channels in magnetic array data, that increased processing system complexity. This paper proposed a processing system for unsaturated magnetic image, the processes included image transformation, filtering and resolution enhancement. This system overcame the shortcomings of interpolation method and digital signal processing. The experimental results showed that every defects could effectively be extracted and a good reconstruction image of multi-frame super-resolution was obtained with 3 simulated sampling intervals. © 2017 ieee.

关键词： image processing Magnetic imageing Super-resolution Wire rope

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Some extensions of the Karnik-Mendel algorithms for computing an interval type-2 fuzzy set centroid

Some extensions of the Karnik-Mendel algorithms for computin...

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ieee/ACM symposium on Advances in Type-2 Fuzzy Logic Systems

作者： Liu, Xinwang Mendel, Jerry M. School of Economics and Management Southeast University Nanjing Jiangsu 210096 China Signal and Image Processing Institute University of Southern California Los Angeles CA 90089-2564 United States

ISBN: (纸本)9781612840789

Computing the centroid of an interval type-2 fuzzy set is an important operation in a type-2 fuzzy logic system, and is usually implemented by Karnik-Mendel (KM) iterative algorithms. This paper proves that the centroid computation of an interval type-2 fuzzy set (IT2 FS) using KM algorithms is equivalent to the Newton-Raphson root-finding method in numerical analysis, and explains how continuous enhanced KM (CEKM) algorithms can be used to compute that centroid. Weighted enhanced KM (WEKM) algorithms are proposed to connect EKM algorithms and CEKM algorithms together using numerical integration techniques. Three new kinds of centroid computation methods are summarized as root finding, CEKM algorithms and WEKM algorithms. Numerical examples illustrate the applications of these new centroid computation methods, and demonstrate the superity of the WEKM algorithms. © 2011 ieee.

关键词： Iterative methods

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RGB image-Based Hand Pose Estimation: A Survey on Deep Learning Perspective 20

RGB Image-Based Hand Pose Estimation: A Survey on Deep Learn...

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20th CSI International symposium on Artificial intelligence and signal processing, AISP 2024

作者： Farjadi, Seyed Amirhossein Akbarzadeh-T, M.-R. Ghiasi-Shirazi, Kamaledin Ferdowsi University of Mashhad Center of Excellence on Soft Computing and Intelligent Information Processing Department of Computer Engineering Mashhad Iran Ferdowsi University of Mashhad Department of Computer Engineering Mashhad Iran

ISBN: (纸本)9798350383942

The pervasive integration of modern artificial intelligence into daily life necessitates robust human-computer interaction, underscored by advancements in computer technology. As the primary human tool, hand position, and orientation are vital for applications like virtual reality, with hand pose estimation playing a pivotal role. Despite the challenges inherent in RGB image-based estimation, the coalescence of extensive datasets, neural networks, and heightened computational capabilities has catalyzed the utilization of deep learning in visual tasks, particularly advancing hand pose estimation. This review exclusively centers on methodologies of RGB image-based approaches within the realm of hand pose estimation. The paper explores recent advancements in this category, providing a comprehensive analysis of outcomes and charting future directions. Organized around discussions on challenges, advancements, and future directions, this review aims to contribute to the ongoing discourse in the dynamic RGB image-based hand pose estimation field. By addressing unique challenges specific to this method, the paper offers insights that contribute to developing precise and robust hand pose estimation systems, impacting the broader landscape of computer vision and human-machine interaction. © 2024 ieee.

关键词： Computer vision

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Enhanced Shot-Based Video Adaptation using MPEG-21 generic Bitstream Syntax Schema

Enhanced Shot-Based Video Adaptation using MPEG-21 generic B...

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Sarah De Bruyne Davy De Schrijver Wesley De Neve Davy Van Deursen Rik Van de Walle Department of Electronics and Information Systems-Multimedia Laboratory-IBBT Ghent University Ledeberg-Ghent Belgium

Semantic video adaptation takes into account the relevance of the different fragments of the video content in order to create a tailored video stream based on the user's preferences. As a shot can be considered as the smallest semantic unit in a video sequence, metadata can be added to each shot using MPEG-7 descriptions. Based on these metadata and the user's preferences, the original bitstream can be adapted in order to obtain the desired fragments. MPEG-21 DIA offers a tool, gBS schema, for exposing the high-level structure of a binary resource as an XML description. In this paper, shot information is inserted in these descriptions to create a link between metadata and semantic video adaptation. Furthermore, this paper proposes to keep the structure of these descriptions format-agnostic. As a result, only one generic transformation style sheet has to be implemented to support shot-based video adaptation of sequences compliant with different video specifications. Special attention is paid to sequences coded with the H.264/AVC standard as this specification contains several interesting features important for shot-based video adaptation

关键词： XML Streaming media Video sequences MPEG 7 Standard computational intelligence Video signal processing Information systems Multimedia systems Automatic voltage control Code standards

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Evolving Fuzzy Rule-based Classifiers

Evolving Fuzzy Rule-based Classifiers

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ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Plamen Angelov Xiaowei Zhou Frank Klawonn Department of Communication Systems InfoLab21 Lancaster University Lancaster UK Department of Computer Science University of Applied Sciences Wolfenbuettel Germany

A novel approach to on-line classification based on fuzzy rules with an open/evolving structure is introduced in this paper. This classifier can start `from scratch', learning and adapting to the new data samples or from an initial rule-based classifier that can be updated based on the new information contained in the new samples. It is suitable for real-time applications such as classification streaming data, robotic applications, e.g., target and landmark recognition, real-time machine health monitoring and prognostics, fault detection and diagnostics, etc. Each prototype is a data sample that represents the focal point of a fuzzy rule per class and is selected based on the data density by an incremental and evolving procedure. This approach is transparent, linguistically interpretable, and applicable to both fully unsupervised and partially supervised learning. It has been validated by two well known benchmark problems and by real-life data in a parallel paper. The contributions of this paper are: i) introduction of the concept of evolving (open structure) classification (eClass) of streaming data; ii) experiments with well known benchmark classification problems (Iris and wine reproduction data sets)

关键词： Fuzzy systems Data mining Knowledge based systems Fault detection Classification tree analysis signal processing Learning systems Decision trees Bayesian methods Evolution (biology)

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