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IEEE Jordan conference on Applied Electrical Engineering and Computing Technologies (AEECT)

作者： Jamal Al-Nabulsi Abdelwadood Mesleh Adnan Yunis Biomedical Engineering Department The Hashemite University Zarqa Jordan Department of Medical Engineering Al-Ahliyya Amman University Amman Jordan Computer Engineering Department Al-Balqa’ Applied university Jordan

This paper proposed an algorithm that detects traffic light colors for colorblind individuals, the proposed algorithm employs image processing techniques associated in image processing toolbox in LabVIEW to help colorblind individuals in identifying the colors of traffic lights. It uses a fixed mobile camera to capture traffic light images taken in different roads and streets in Jordan and Kuwait. It detects traffic lights by comparing the candidate traffic light with some in-house collected traffic light templates, comparison is based on correlation. The templates represent 22 different shapes of traffic lights in Jordan and Kuwait. Finally, the algorithm extracts the green and the red planes and recognizes their colors. Experimental results reveal the accuracy of proposed algorithm in identifying the colors of traffic lights in different cases and circumstances. Hence, our proposed algorithm is helpful for colorblind drivers.

关键词： image color analysis Cameras Vehicles Vision defects image recognition Detection algorithms Real-time systems

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ProxImaL: Efficient image Optimization using Proximal algorithms

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ACM TRANSACTIONS ON GRAPHICS 2016年第4期35卷 1-15页

作者： Heide, Felix Diamond, Steven Niessner, Matthias Ragan-Kelley, Jonathan Heidrich, Wolfgang Wetzstein, Gordon Stanford Univ Stanford CA 94305 USA Univ British Columbia Vancouver BC V5Z 1M9 Canada KAUST Thuwal Saudi Arabia

Computational photography systems are becoming increasingly diverse, while computational resources-for example on mobile platforms-are rapidly increasing. As diverse as these camera systems may be, slightly different variants of the underlying image processing tasks, such as demosaicking, deconvolution, denoising, inpainting, image fusion, and alignment, are shared between all of these systems. Formal optimization methods have recently been demonstrated to achieve state-of-the-art quality for many of these applications. Unfortunately, different combinations of natural image priors and optimization algorithms may be optimal for different problems, and implementing and testing each combination is currently a time-consuming and error-prone process. ProxImaL is a domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety of linear and nonlinear image formation models and cost functions, advanced image priors, and noise models. The compiler intelligently chooses the best way to translate a problem formulation and choice of optimization algorithm into an efficient solver implementation. In applications to the image processing pipeline, deconvolution in the presence of Poisson-distributed shot noise, and burst denoising, we show that a few lines of ProxImaL code can generate highly efficient solvers that achieve state-of-the-art results. We also show applications to the nonlinear and nonconvex problem of phase retrieval.

关键词： computational photography digital image processing optimization

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Automatic traffic sign detection and recognition using moment invariants and support vector machine

Automatic traffic sign detection and recognition using momen...

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

作者： Sneha Agrawal Rahul Kumar Chaurasiya Department of Information Technology National Institute of Technology Raipur Raipur India Department of Electronics & Telecommunication National Institute of Technology Raipur Raipur India

ISBN: (纸本)9781509047611;9781509047604

Automatic traffic sign detection and recognition (TSDR) is one of the most significant areas of object detection. In spite of numerous researches, it has always been a challenging problem. In this paper, an approach for detecting circular and triangular traffic signs is proposed. The performance of the entire system is measured on German traffic sign detection benchmark (GTSDB) and German traffic sign recognition benchmark (GTSRB) dataset. Traffic signs are detected using color segmentation and thresholding method in Hue Saturation Intensity (HSI) color space. Then, the shape of traffic signs is detected using geometric invariant Hu moments. Further, the features are extracted using a technique called HSI-HOG descriptor where features are extracted from each channel of HSI independently. To select the most discriminant features with minimal loss of information, dimensionality reduction technique Principal Component Analysis (PCA) is applied and classification is performed using Support Vector Machine (SVM) technique.

关键词： image color analysis Shape Feature extraction image segmentation Lighting Support vector machines Classification algorithms

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IPI NOISE REDUCTION BY image MASK USING DNA CODING METHOD IN HOLOGRAPHIC DATA STORAGE SYSTEM

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ASME conference on Information Storage and processing systems

作者： Kim, Jang Hyun Yang, Hyunseok Yonsei Univ Ctr Informat Storage Device Seoul 03722 South Korea Yonsei Univ Sch Mech Engn Seoul 03722 South Korea

ISBN: (纸本)9780791849880

A holographic data storage system(HDSS) is very important field in the storage system device. Many researchers study the HDSS about image processing algorithm for reduction of image noise. In this work, we proposed an intelligence virtual mask, parameter values of virtual image mask generated using DNA coding method, it is available to decrease the IPI noise in HDSS. In this paper, an intensity distribution of laser beam in our HDSS is controlled by the virtual mask with an intelligence algorithm. The virtual mask value is changed arbitrarily in real-time with suggested DNA coding method in the HDSS.

关键词： algorithms Noise control Data storage systems Noise (Sound) Laser beams DNA Storage image processing

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ANFIS based Color Constancy algorithms Selection System for Dark image Enhancement

ANFIS based Color Constancy Algorithms Selection System for ...

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International conference on Next Generation Intelligent systems (ICNGIS)

作者： Thasni, A. N. Deepthi, V. R. Francis, Ann Bonia RIT Dept CSE Kottayam Kerala India

ISBN: (纸本)9781509008704

This work introduces an Artificial Neuro-Fuzzy Inference System functioning as a selector of color constancy algorithms for the enhancement of dark images. The system selects among three algorithms, the White-Patch, the Gray-World and the Gray-Edge according to real content of an image. These three algorithms have been considered due to their simplicity and accurate remotion of the illuminant, further showing an outstanding color enhancement on images. The diverse image features are involved in the selection process, so the design of selector system is not a trivial task. For this reason we developed a fuzzy rule based system to model the information through simple rules. While addressing the problem of dark image enhancement this approach can handle large amount of data and is tolerant to ambiguity.

关键词： Fuzzy logic Color constancy image processing image enhancement

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A modified technique for smart textural feature selection to extract retinal regions of interest using image pre-processing

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Journal of Physics: conference Series 2018年第1期1096卷

作者： N Yu Ilyasova A S Shirokanev R A Paringer A V Kupriyanov A V Zolotarev Samara National Research University Moskovskoe shosse st. 34 Samara Russia 443086 Image Processing Systems Institute - Branch of the Federal Scientific Research Centre 'Crystallography and Photonics' of Russian Academy of Sciences Molodogvardeyskaya str. 151 Samara Russia 443001 Samara State Medical University Chapayevskaya st. 89 Samara Russia 443066

To increase the efficiency of the laser coagulation surgery the problem of the most accurate segmentation of fundus images is especially relevant. Fundus image segmentation is carried out with high accuracy using effective features and the minimum number of parameters for segmentation of a single image fragment. This paper describes a modified technique for smart textural feature selection to extract retinal regions of interest using image preprocessing algorithms. Preprocessing algorithms significantly influence the selected features which provide a minimum error of object recognition. In addition image preprocessing algorithms provide a more precise object selection. The informativeness of the obtained feature space is studied using discriminant data analysis. The best fragmentation block size segmentation and feature sets provides the necessary accuracy to identify regions of interest. Those regions are determined by the analysis of the following 4 classes of fundus images: exudates, thick, thin vessels and healthy areas. The advantages and disadvantages of the considered preprocessing algorithms were identified.

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

Control methods for piezomechanical robots moving in traject...

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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...

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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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