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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems IV"

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Control methods for piezomechanical robots moving in trajectories: Software and hardware

Control methods for piezomechanical robots moving in traject...

引用

Electrical, Electronic and Information Sciences (eStream), Open conference of

作者： Eugenijus Macerauskas Jurate Janutenaite-Bagdoniene Genadijus Kulvietis Department of Information Technologies Vilnius Gediminas technical university Vilnius Lithuania

ISBN: (纸本)9781538639993

Practical application of smart materials for moving robots enabled to solve difficult mechatronic positioning and movement problems. Movement in such systems is generated using piezoelectrical devices. Therefore, classical trajectories formation and control methods are not suitable. For these specific problems positioning and piezorobot control methods and algorithms are created. In order to practically realize these algorithms a novel software and hardware is needed. This article presents movement formation methods and movement in predefined trajectory on some plane algorithms for cylindrical piezorobot. It is shown how they can be implemented using Matlab and LabVIEW software. Trajectory movement is controlled using special software and specifically designed motion control system. Control signal is amplified by electronics hardware. It also matches industrial PXI computer to piezorobot's motion actuator which requires high voltage signal and capacitance load. The path of piezorobot is registered using image processing and computer vision technologies. The paper presents experimental results of piezorobot movement when different input data set applied. Piezorobot point-to-point movement on plane without rotation is analyzed. Such movement is created when only one electrode is excited at a time. This generates forces at every segment and their cumulative force ensures precise control of piezorobot movement direction and speed.

关键词： Trajectory MATLAB Force Monitoring Robots image processing

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Vehicle detection and identification in an unconstrained environment

Vehicle detection and identification in an unconstrained env...

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International conference on Recent Innovations in Signal processing and Embedded systems (RISE)

作者： Lavanya Herle Poonam Sharma Department of Computer Science and Engineering Visvesvarya National Institute of Technology Nagpur

ISBN: (纸本)9781509047611;9781509047604

Detection and identification of vehicles in traffic surveillance videos is very important to automate the surveillance system and also to build an intelligent transportation system. In this paper a robust method to detect and identify vehicles is proposed which deals with problem like change in illumination. Background subtraction is done using both Gaussian Mixture Model and Visual Background Extractor and supports dynamic changes in background. Vehicles are detected by finding contours in the image frame. Vehicles are tracked by assigning unique ID for each vehicles. Distance between the centroid of detected vehicle and existing vehicles is calculated. If the distance is greater than threshold value then vehicle is considered to be arrived newly and a unique ID is assigned for further tracking. Otherwise, it is the vehicle will get the same ID as in previous frame. Detected vehicle is classified using Support Vector Machine in each frame and final decision is taken when the vehicle is about to exit from the scene.

关键词： Support vector machines Feature extraction Surveillance Vehicle detection Traffic control Videos Classification algorithms

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Hessian-Assisted Supervoxel: Structure-Oriented Voxel Clustering and Application to Mediastinal Lymph Node Detection from CT Volumes

Hessian-Assisted Supervoxel: Structure-Oriented Voxel Cluste...

引用

conference on Medical Imaging - Computer-Aided Diagnosis

作者： Oda, Hirosha Bhatia, Kanwal K. Oda, Masahiro Kitasaka, Takayuki Iwano, Shingo Homma, Hirotoshi Takabatake, Hirotsugu Mori, Masaki Natori, Hiroshi Schnabel, Julia A. Mori, Kensaku Nagoya Univ Grad Sch Informat Sci Nagoya Aichi Japan Kings Coll London Div Imaging Sci & Biomed Engn London England Nagoya Univ Strategy Off Informat & Commun Nagoya Aichi Japan Aichi Inst Technol Fac Informat Sci Toyota Japan Nagoya Univ Grad Sch Med Nagoya Aichi Japan Sapporo Kosei Gen Hosp Sapporo Hokkaido Japan Sapporo Minami Sanjo Hosp Sapporo Hokkaido Japan Keiwakai Nishioka Hosp Nagoya Aichi Japan

ISBN: (纸本)9781510607132;9781510607149

In this paper, we propose a novel supervoxel segmentation method designed for mediastinal lymph node by embedding Hessian-based feature extraction. Starting from a popular supervoxel segmentation method, SLIC, which computes supervoxels by minimising differences of intensity and distance, we overcome this method's limitation of merging neighboring regions with similar intensity by introducing Hessian-based feature analysis into the supervoxel formation. We call this structure-oriented voxel clustering, which allows more accurate division into distinct regions having blob-, line- or sheet-like structures. This way, different tissue types in chest CT volumes can be segmented individually, even if neighboring tissues have similar intensity or are of non- spherical extent. We demonstrate the performance of the Hessian-assisted supervoxel technique by applying it to mediastinal lymph node detection in 47 chest CT volumes, resulting in false positive reductions from lymph node candidate regions. 89 % of lymph nodes whose short axis is at least 10 mm could be detected with 5.9 false positives per case using our method, compared to our previous method having 83 % of detection rate with 6.4 false positives per case. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

关键词： Lymphatic system image segmentation Blood vessels Chest Esophagus Feature extraction Target detection Computer aided diagnosis and therapy Information science Computer-aided diagnosis image processing algorithms and systems Lung Lung cancer

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Non-iterative Filter Bank Phase (Re)Construction

Non-iterative Filter Bank Phase (Re)Construction

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European Signal processing conference

作者： Zdenek Prusa Nicki Holighaus Austrian Academy of Sciences Acoustics Research Institute Vienna Austria

Signal reconstruction from magnitude-only measurements presents a long-standing problem in signal processing. In this contribution, we propose a phase (re)construction method for filter banks with uniform decimation and controlled frequency variation. The suggested procedure extends the recently introduced phase-gradient heap integration and relies on a phase-magnitude relationship for filter bank coefficients obtained from Gaussian filters. Admissible filter banks are modeled as the discretization of certain generalized translation-invariant systems, for which we derive the phase-magnitude relationship explicitly. The implementation for discrete signals is described and the performance of the algorithm is evaluated on a range of real and synthetic signals.

关键词： Signal processing algorithms Time-frequency analysis Phase measurement Europe image reconstruction Filter banks

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A Research Tool for the Power and Performance Analysis of Sensor-Based Mobile Robots 1

A Research Tool for the Power and Performance Analysis of Se...

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1st New Generation of CAS conference (NGCAS )

作者： Harris, Christopher B. Bahar, R. Iris Auburn Univ Dept Elect & Comp Engn Auburn AL 36849 USA Brown Univ Sch Engn Providence RI 02912 USA

ISBN: (纸本)9781509064472

Contemporary sensor-based robotic systems tend to use an ad-hoc combination of off-the-shelf components for onboard computational needs. The number and type of sensors present, the number and organization of the onboard processors, and the algorithms utilized for processing high bandwidth real-time sensor data present researchers and designers with a wide range of choices for which they are currently ill-equipped to evaluate the best options. We present a co-simulation framework for sensor-based mobile robots that allows for the power and performance analysis of custom embedded computing platforms for mobile robots with a range of onboard sensors. We demonstrate the utility of our co-simulation framework by analyzing the power and performance tradeoffs for the computational subsystem of a quadrotor unmanned aerial vehicle (UAV) with onboard camera sensor performing image processing tasks while operating in a custom virtual testbed.

关键词： Robot sensing systems Computational modeling Cameras image sensors Solid modeling

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Surface reconstruction with Wavelet transformation 20

Surface reconstruction with Wavelet transformation

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20th Jubilee IEEE International conference on Intelligent Engineering systems (INES)

作者： Balla, Petra Kocsis, Peter Eigner, Gyorgy Antal, Akos BUTE Dept Mechatron Opt & Mech Engn Informat Budapest Hungary Obuda Univ Res & Innovat Ctr Physiol Controls Grp Budapest Hungary

ISBN: (纸本)9781509012169

The development in computing power highlights some forgotten algorithms, which were neglected because of their complexity and slowness on early computers. One example is the Wavelet-Transformation Profilometry (WTP) of which successful application is demonstrated in the paper. WTP is a high level signal processing method using orthogonal algorithms for huge datasets. The high performance in quality and running speed makes the described method suitable for medical image processing applications.

关键词： processing

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Detection of Face Position and Orientation Using Depth Data

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8th International conference on image processing and Communications (IP and C)

作者： Szwoch, Mariusz Pieniazek, Pawel Gdansk Univ Technol Gdansk Poland

ISBN: (纸本)9783319238142;9783319238135

In this paper an original approach is presented for real-time detection of user's face position and orientation based only on depth channel from a Microsoft Kinect sensor which can be used in facial analysis on scenes with poor lighting conditions where traditional algorithms based on optical channel may have failed. Thus the proposed approach can support, or even replace, algorithms based on optical channel or based on skeleton or face tracking information. The accuracy of proposed algorithms is 91% and was verified on Facial Expressions and Emotions Database using 169 recordings of 25 persons. As the processing time is below 20 ms per frame on a standard PC, the proposed algorithms can be used in real-life applications. The presented algorithms were validated in a prototype application for user emotion recognition based on depth channel information only.

关键词： Face detection Depth image processing Kinect sensor

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Improving the compression efficiency for transform video coding

Improving the compression efficiency for transform video cod...

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International conference on systems and Informatics (ICSAI)

作者： Jianyu Lin Department of Electronic Engineering Guangdong Provincial key Laboratory of Digital Signal and Image Processing Guangdong P. R. China

A new 3D transform video coding algorithm is introduced, which does not use motion compensation. More independent and highly efficient algorithms are employed for each key step of the transform coding. For the transform step, the SCWP (Spectral Condensed Wavelet Packet) is adopted. For the quantization step, a trimming process is implemented, which keeps the bit allocation function of the significant propagation technique but is independent from the entropy coding step. For the entropy coding step, a novel entropy coding technique based upon binary run-length coding is proposed. This binary entropy coding can be applied to multiple symbol source coding, and it approaches an optimal efficiency bound which is within 1.5% of the source entropy when the source approaches iid. Principally, the complexity of the proposed transform video coding algorithm is comparable to that of a 2D still image transform coding algorithm. However, its compression performance is competitive to HEVC at high compression bitrates.

关键词： image coding Bit rate Transforms Encoding Algorithm design and analysis Video coding Three-dimensional displays

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image Sharpness Assessment Based on Local Phase Coherence and LAD Criterion 23

Image Sharpness Assessment Based on Local Phase Coherence an...

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23rd International conference on systems, Signals and image processing (IWSSIP)

作者： Krzic, Ana Sovic Donlic, Matea Pejcinovic, Mihaela Sersic, Damir Univ Zagreb Fac Elect Engn & Comp Unska 3 Zagreb 10000 Croatia Poslovna Inteligencija Zelinska 4 Zagreb 10000 Croatia

ISBN: (纸本)9781467395557

Edge preservation and precise restoration of details and sharp parts of images is an important issue in modern multimedia systems, 3D imaging, medical imaging and laser microscopy. Objective evaluation of image restoration algorithms in the sense of sharpness is crucial for choice of method to be used. Moreover, automated focus stacking, selective deblurring and other smart restoration methods rely on the proper sharpness measure. In this paper, a novel approach for image sharpness assessment is proposed. The approach is based on local phase coherence (LPC) in the complex wavelet domain. Using maximum pooling of eight LPC maps in eight spatial directions around each pixel, an image sharpness map is generated. Least absolute deviation criterion applied on sorted non-zero elements of the sharpness map results in the proposed global image sharpness measure. The proposed measure is better suited for applications, in comparison with competitive measures.

关键词： Sharpness Assessment Sharpness Measure Blurriness Local Phase Coherence

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Tukey's Biweight constrain function for a surrogate image enlargement based on SISR algorithm using high spectrum estimation

Tukey's Biweight constrain function for a surrogate image en...

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International conference of Information and Communication Technology for Embedded systems (IC-ICTES)

作者： Kornkamol Thakulsukanant Vorapoj Patanavijit Assumption University of Thailand Thailand

ISBN: (纸本)9781509048106

Consistently, the classical image enlargement algorithm is a scientific analytical method for producing a better refined resolution image that is frequently required for advanced digital image processing (DIP) from a single lower resolution image that is frequently acquired from digital camera embedded system. Because of its less computation calculation, the Single-image Super-Resolution (SISR) that analytically applied for a single lower resolution image is one of the worldwide effective Super Resolution-Reconstruction (SRR) algorithms thus this paper proposes the image enlargement based on the SISR algorithm using high spectrum estimation and Tukey's Biweight constrain function. In general, the performance of this SISR algorithm is hinge on up to three parameters (b, h, k) however there are burdensome for determining these optimized values for these parameters (b, h, k). In order to solve this problem, the Tukey's Biweight constrain function, which is hinge on merely single parameter (T), contrary to three parameters like the classical constrain function, is engaged in the SISR algorithm. By examining on 14 benchmark images, which are profaned by considerable noise forms, in scientific analytical scrutinizing sector, the novel SISR algorithm illustrates that there is efficiently and effortlessly in parameter setting process but the performance of the novel SISR algorithm (with single parameters) is nearly equal to the original SISR (with three parameters). Due to greatly time reduction in the parameter setting process, this novel SISR algorithm is more advisable for real-time applications.

关键词： image resolution Algorithm design and analysis Spectral analysis Estimation Fasteners Digital images Benchmark testing

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