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

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Autocollimation sensor for measuring the deformations of objects and modules containing environmentally hazardous substances 4

Autocollimation sensor for measuring the deformations of obj...

引用

conference on Optical Sensing and Detection iv

作者： Konyakhin, Igor A. Malishev, Alexey V. Van Phong Hoang ITMO Univ Dept Opt Elect Devices & Syst 49 Kronverkskiy Pr St Petersburg Russia

ISBN: (纸本)9781510601444

The article is based on some researching considering the three-axis angle measuring autocollimation sensor. Such a sensor allows measuring the deformation of large constructed objects while receiving the information about all three angular freedom degrees. The feasibility of a special tetrahedral prism reflector, with two modes of operation is described and proved. The ability to synthesize such a reflector is proved mathematically;including the description of it's both modes functioning. All algorithms were taken from the mathematical model of such a reflector functioning, which was created while the researching. First mode allows measuring the roll angle with high accuracy, and the second mode allows measuring the collimation angles, using different types of light reflected beams. So there are two ways to measure collimation angles: rough and precise. The algorithm for rough way of collimation angles measuring is quite similar to the roll algorithm measuring and used for the adjustment and for the initial setting the autocollimation sensor. The precise algorithm is used for the prime measuring in a complex with roll angle measuring to get full information of three-dimensional deformation of the object. The experimental stand was researched to confirm the correctness of all algorithms of the reflector and the sensor functionality in the whole. The technical characteristics of the experimental setup are presented.

关键词： environmentally hazardous facilities autocollimation sensor pitch yaw and roll measurements tetrahedral reflector matrix photo receiver invariant axis image processing three-dimension deformations

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Improving the Performance of Vehicle Detection System in Bad Weathers

Improving the Performance of Vehicle Detection System in Bad...

引用

2016 IEEE Advanced Information Management,Communicates,Electronic and Automation Control conference(IMCEC 2016)

作者： Xuerui Dai Xue Yuan Jing Zhang Liping Zhang School of electronic and Information Beijing Jiaotong University Naval Aeronautical Engineering Institute Beijing Huahang Radio Measurement Institute

ISBN: (纸本)9781509001668

Vehicle detection has been applied in many fields,such as intelligent transportation,video surveillance,driving assistance system and so *** the case of fine weather,the state-of-the-art vehicle-detection systems may achieve good ***,the performance has a substantial decline in bad weathers,such as fog,night and so ***,improving the performance of vehicle-detection systems in different weather conditions becomes an important issue in vehicle-detection *** the fog or night,the quality of the images is *** this paper,we propose some algorithms of image defogging and color enhancement in order to improve the performance of vehicle *** result of vehicle detection get much better after image processing in bad weathers.

关键词： Vehicle detection bad weathers image defogging color enhancement

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Automation of Solar System for Maximum Power Point Tracking using IoT 16

Automation of Solar System for Maximum Power Point Tracking ...

引用

1st International conference on Informatics and Analytics (ICIA)

作者： Sujatha, K. Ponmagal, R. S. Godhavari, T. Dr MGR Educ & Res Inst Ctr Elect Automat & Ind Res CEAIR EEE Dept Chennai Tamil Nadu India Dr MGR Educ & Res Inst CSE Dept Chennai Tamil Nadu India Dr MGR Educ & Res Inst ECE Dept Chennai Tamil Nadu India

ISBN: (纸本)9781450347563

The importance of this paper focuses on the efficiency of the solar panel which can be increased by incorporating indigenous solar tracking systems in order to increase solar panel efficiency. The implementation necessitates precise control which is important to build a refined tracking system. A solar tracking system with Artificial Neural Network (ANN) based image processing (IPT) Techniques to estimate the astronomical aspects of the sun from Global Positioning System (GPS) and machine vision image sensor is proposed here. The features extracted using IP algorithms with a decision making AI process is adopted to differentiate whether the present weather condition is sunny or cloudy. With reference to the results obtained, the solar tracking system establishes the usage of astronomical calculations approximately. The proposed hi-tech arrangement is evaluated and validated through experimentation results which are made available on the cloud service for coordination.

关键词： Internet of Things Automatic solar tracking system image processing Artificial neural networks Maximum power point tracking cloud computing

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Design of Smartphone-Based Wound Assessment System 1

Design of Smartphone-Based Wound Assessment System

引用

International conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT)

作者： Dalya, Vidyashree Shedge, D. K. AISSMSs Inst Informat Technol Dept Elect Engn Pune Maharashtra India AISSMSs Inst Informat Technol Pune Maharashtra India

ISBN: (纸本)9781509020805

The physical condition that affects the way the human body processes sugar (glucose) is known as diabetes. It is an alarming issue and is one of the major causes to prolong human wounds. Wounds examination process involves an expertise and constant follow ups to check and recommend wound details. This is a costly process and troublesome in case of bed ridden patients. Various systems like MEdical Digital PHOtogrammetric System (MEDPHOS), Measurement of Area and Volume Instrument System (MAVIS) have been developed for wound assessment. The systems suffer from high cost and maintenance. Moreover, these also need an expertise to perform assessment. As smart phones have become the part and parcel of our lives,, this project attempts to make use of Smart phones with a high-resolution digital camera, assessing wounds by analyzing images of chronic foot ulcers. In this paper, we have developed an android based smartphone based solution involving the patients or hospital nurses actively. Additionally, we have also developed an online "Experts review" system which would send the image analysis notifications to the user. The proposed system consist of an android-based PC application. The user captures the image and uploads the image to the database. The image is then processed against the K-shift algorithm. The inferences like the wound status are then sent to the user and the image is also sent for expert review. The experts then examine the image, and based on the status of the wounds, they suggest for any changes in the treatment. Our simulation results show that the wound detection using K-mean shift algorithms gave good accuracy of approximately 80%. This shows that with this smart phone system provides promising accuracy for wound image analysis.

关键词： diabetes android based smartphone mean shift image processing

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The Cropland Capture Game: Good Annotators Versus Vote Aggregation Methods 4th

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4th International conference on Computer Science, Applied Mathematics and Applications (ICCSAMA)

作者： Baklanov, Artem Fritz, Steffen Khachay, Michael Nurmukhametov, Oleg See, Linda Int Inst Appl Syst Anal Laxenburg Austria Krasovsky Inst Math & Mech Ekaterinburg Russia Ural Fed Univ Ekaterinburg Russia

ISBN: (纸本)9783319388847;9783319388830

The Cropland Capture game, which is a recently developed Geo-Wiki game, aims to map cultivated lands using around 17,000 satellite images from the Earth's surface. Using a perceptual hash and blur detection algorithm, we improve the quality of the Cropland Capture game's dataset. We then benchmark state-of-the-art algorithms for an aggregation of votes using results of well-known machine learning algorithms as a baseline. We demonstrate that volunteer-image assignment is highly irregular and only good annotators are presented (there are no spammers and malicious voters). We conjecture that the last fact is the main reason for surprisingly similar accuracy levels across all examined algorithms. Finally, we increase the estimated consistency with expert opinion from 77 to 91% and up to 96% if we restrict our attention to images with more than 9 votes.

关键词： Crowdsourcing image processing Votes aggregation

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Anatomy-Aware Measurement of Segmentation Accuracy

Anatomy-Aware Measurement of Segmentation Accuracy

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conference on Medical Imaging - image processing

作者： Tizhoosh, H. R. Othman, A. A. Univ Waterloo KIMIA Lab 200 Univ Ave West Waterloo ON Canada Suez Canal Univ Dept Informat Syst Comp & Informat Ismailia Egypt

ISBN: (纸本)9781510600195

Quantifying the accuracy of segmentation and manual delineation of organs, tissue types and tumors in medical images is a necessary measurement that suffers from multiple problems. One major shortcoming of all accuracy measures is that they neglect the anatomical significance or relevance of different zones within a given segment. Hence, existing accuracy metrics measure the overlap of a given segment with a ground-truth without any anatomical discrimination inside the segment. For instance, if we understand the rectal wall or urethral sphincter as anatomical zones, then current accuracy measures ignore their significance when they are applied to assess the quality of the prostate gland segments. In this paper, we propose an anatomy-aware measurement scheme for segmentation accuracy of medical images. The idea is to create a "master gold" based on a consensus shape containing not just the outline of the segment but also the outlines of the internal zones if existent or relevant. To apply this new approach to accuracy measurement, we introduce the anatomy-aware extensions of both Dice coefficient and Jaccard index and investigate their effect using 500 synthetic prostate ultrasound images with 20 different segments for each image. We show that through anatomy-sensitive calculation of segmentation accuracy, namely by considering relevant anatomical zones, not only the measurement of individual users can change but also the ranking of users' segmentation skills may require reordering.

关键词： image segmentation Gold Prostate Magnesium image processing algorithms and systems Tumors Ultrasonography Buildings Accuracy assessment Shape analysis

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Development of brain-controlled wheelchair supported by raspicam image processing based Raspberry pi

Development of brain-controlled wheelchair supported by rasp...

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International conference on Automation, Cognitive Science, Optics, Micro Electro-Mechanical System, and Information Technology (ICACOMIT)

作者： Arjon Turnip Taufik Hidayat Dwi Esti Kusumandari Technical Implementation Unit for Instrumentation Development Indonesian Institute of Sciences Bandung Indonesia

Helping a disable subject for improving their quality of life and providing them a priorit care at the right time is one of the most important things for us a responsible member of researcher. Hence there is a need for developing a wheelchair that is intelligent, provides easy maneuverability, and safety to drive. A brain intelligent wheelchair, which uses the recorded signals from the brain and processes it to control the wheelchair has been designed. However, it has not yet been widely adopted, and any commercial device would need proper safety trials and approval before release. In this paper, a smart wheelchair based bio-signal & non bio-signal approach which translated into movement commands by the arduino microcontroller is proposed. Four ultrasonics sensor, a raspicam for obstacle detection, and Inertial Measurement Unit for speed controller on sloping road are integrated with the wheelchair based biosignals called brain-controlled wheelchair. The performance improvement of the of the obstacle avoidance are examinated. The evaluation of the wheelchair movement is performed under real conditions using direction and speed control commands of the wheelchair. It is obtained that the misclassification is reduced and the accuracy is increased.

关键词： Wheelchairs Robot sensing systems Feature extraction Acoustics Classification algorithms DC motors

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Local Gabor Wavelet-Based Feature Extraction and Evaluation 3rd

Local Gabor Wavelet-Based Feature Extraction and Evaluation

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3rd International conference on Advanced Computing, Networking, and Informatics (ICACNI)

作者： Malathi, T. Bhuyan, M. K. Indian Inst Technol Dept Elect & Elect Engn Gauhati 781039 India

ISBN: (纸本)9788132225386;9788132225379

Feature extraction is an essential step in many image processing and computer vision applications. It is quite desirable that the extracted features can effectively represent an image. Furthermore, the dominant information visually perceived by human beings should be efficiently represented by the extracted features. Over the last few decades, different algorithms are proposed to address the major issues of image representations by the efficient features. Gabor wavelet is one of the most widely used filters for image feature extraction. Existing Gabor wavelet-based feature extraction methodologies unnecessarily use both the real and the imaginary coefficients, which are subsequently processed by dimensionality reduction techniques such as PCA, LDA etc. This procedure ultimately affects the overall performance of the algorithm in terms of memory requirement and the computational complexity. To address this particular issue, we proposed a local image feature extraction method by using a Gabor wavelet. In our method, an image is divided into overlapping image blocks, and subsequently each of the image blocks are separately filtered out by Gabor wavelet. Finally, the extracted coefficients are concatenated to get the proposed local feature vector. The efficacy and effectiveness of the proposed feature extraction method is evaluated using the estimation of mean square error (MSE), peak signal-to-noise ratio (PSNR), and the correlation coefficient (CC) by reconstructing the original image using the extracted features, and compared it with the original input image. All these performance evaluation measures clearly show that real coefficients of the Gabor filter alone can effectively represent an image as compared to the methods which utilize either the imaginary coefficients or the both. The major novelty of our method lies on our claim-capability of the real coefficients of a Gabor filter for image representation.

关键词： image feature extraction Gabor filter image reconstruction

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GPGPU based Concurrent Classification using Trained Model of Handwritten Digits

GPGPU based Concurrent Classification using Trained Model of...

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10th International conference on Open Source systems and Technologies (ICOSST)

作者： Rizvi, Syed Tahir Hussain Cabodi, Gianpiero Arif, Arslan Javed, Muhammad Yaqoob Gulzar, Muhammad Majid Politecn Torino Turin Italy Univ Sci & Technol China Hefei Peoples R China Univ Cent Punjab Lahore Pakistan

ISBN: (纸本)9781509055869

In this paper, General Purpose Graphical processing Unit (GPGPU) based concurrent implementation of handwritten digit classifier is presented. Different styles of handwriting make it difficult to recognize a pattern but using neural network, it is not a difficult task to perform. Different softwares like torch and MATLAB provide the support of multiple training algorithms to train a network. By choosing an appropriate training algorithm for a specific application, speed of training can be increased. Furthermore, using computational power of GPUs, training and classification speed of neural network can be significantly improved. In this work, Modified National Institute of Standards and Technology (MNIST) database of handwritten digits is used to train the network. Accuracy and training time of digit classifier is evaluated for different algorithms and then concurrent training is performed by exploiting power of GPU. Trained parameters are imported and used for the concurrent classification with Compute Unified Device Architecture (CUDA) computing language which can be useful in numerous practical applications. Finally, the results of sequential and concurrent operations of training and classification are compared.

关键词： Concurrent Parallel architectures Neural network Pattern recognition MATLAB image Classification

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Traffic Signs Detection Using Tracking with Prediction 1

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12th International Joint conference on E-Business and Telecommunications (ICETE)

作者： Yakimov, Pavel Samara State Aerosp Univ 34 Moskovskoye Shosse Samara Russia Russian Acad Sci Image Proc Syst Inst 151 Molodogvardeyskaya St Samara Russia

ISBN: (数字)9783319302225

ISBN: (纸本)9783319302225;9783319302218

This paper proposes an efficient algorithm for real-time traffic sign detection. The article considers the practicability of using HSV color space to extract the red color. An algorithm to remove noise to improve the accuracy and speed of detection was developed. A modified Generalized Hough transform is then used to detect traffic signs. The current velocity of a vehicle is used to predict the sign's location in the adjacent frames in a video sequence. Finally, the detected objects are being classified. The detection and classification of road signs algorithms are implemented using CUDA and operate in real time on an Android device. The developed algorithms have been tested using real scene images and the German Traffic Sign Detection Benchmark (GTSDB) dataset and showed efficient results.

关键词： Traffic signs detection Advanced driver assistance systems Computer vision Graphics processing units image processing Pattern Recognition

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