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

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Road Sign Recognition System on Raspberry Pi

Road Sign Recognition System on Raspberry Pi

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IEEE Long Island systems, Applications and Technology conference (LISAT)

作者： Bilgin, Enis Robila, Stefan Montclair State Univ Dept Comp Sci Montclair NJ 07043 USA

ISBN: (纸本)9781467384902

Digital image processing, i.e. the use of computer systems to process pictures, has applications in many fields, including of medicine, space exploration, geology and oceanography and continues to increase in its applicability. The main objective of this paper is to demonstrate the ability of image processing algorithms on a small computing platform. Specifically we created a road sign recognition system based on an embedded system that reads and recognizes speed signs. The paper describes the characteristics of speed signs, requirements and difficulties behind implementing a real-time base system with embedded system, and how to deal with numbers using image processing techniques based on shape and dimension analysis. The paper also shows the techniques used for classification and recognition. Color analysis also plays a specifically important role in many other different applications for road sign detection, this paper points to many problems regarding stability of color detection due to daylight conditions, so absence of color model can led a better solution. In this project lightweight techniques were mainly used due to limitation of real-time based application and Raspberry Pi capabilities. Raspberry Pi is the main target for the implementation, as it provides an interface between sensors, database, and image processing results, while also performing functions to manipulate peripheral units (usb dongle, keyboard etc.).

关键词： component Digital image processing Raspberry Pi Embedded System Road Sign Recognition

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processing of data from the camera of structured light for algorithms of image analysis in control systems of mobile robots

引用

International conference on Modern Engineering: Science and Education, MESE 2011

作者： Skakunov, Vladimir Belikov, Victor Zhoga, Victor Nesmiynov, Ivan Volgograd State Technical University Volgograd Russia Volgograd State Agrarian University Volgograd Russia

ISBN: (纸本)9783319295787

The article discusses the preprocessing algorithms of three-dimensional clouds of points from structured light cameras, methods of image recognition, algorithms for constructing maps and route planning for robot motion. Various methods and algorithms for the transformation of a three-dimensional cloud of points leads to reduction of computational complexity of all stages of data processing for implementation of the algorithm on an onboard navigation system with limited computing resources. Based on the proposed sequence of image conversion, software has been developed for implementation of the algorithm of spatial orientation of a robot. image processing methods and functions of PCL and ROS metapackage libraries were used. Experimental study of the possibilities of the developed image processing and route construction algorithm was made using the prototype of a mobile robot on a wheeled platform. © Springer International Publishing Switzerland 2016.

关键词： 3D point clouds Mobile robot Navigation algorithms Pattern recognition algorithms Structured-light camera Supervisory management

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Real-time Combustion State Identification via image processing: A Dynamic Data-Driven approach

Real-time Combustion State Identification via Image Processi...

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American Control conference (ACC)

作者： Hauser, Michael Li, Yue Li, Jihang Ray, Asok Penn State Univ Mech & Nucl Engn Dept University Pk PA 16802 USA

ISBN: (纸本)9781467386821

This paper proposes a framework for analyzing video of physical processes as a paradigm of dynamic data-driven application systems (DDDAS). The algorithms were tested on a combustion system under fuel lean and ultra-lean conditions. The main challenge here is to develop feature extraction and information compression algorithms with low computational complexity such that they can be applied to real-time analysis of video captured by a high-speed camera. In the proposed method, image frames of the video is compressed into a sequence of image features. then, these image features are mapped to a sequence of symbols by partitioning of the feature space. Finally, a special class of probabilistic finite state automata (PFSA), called D-Markov machines, are constructed from the symbol strings to extract pertinent features representing the embedded dynamic characteristics of the physical process. This paper compares the performance and efficiency of three image feature extraction algorithms: Histogram of Oriented Gradients, Gabor Wavelets, and Fractal Dimension. The k-means clustering algorithm has been used for feature space partitioning. The proposed algorithm has been validated on experimental data in a laboratory environment combustor with a single fuel-injector.

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Identifying and classifying cancerous cells based on the Ki67 detector 2

Identifying and classifying cancerous cells based on the Ki6...

引用

2nd International conference on image processing, Applications and systems (IPAS)

作者： Seddik, Hassen Saidani, Bechir Univ Tunis ENSIT Tunis Tunisia

ISBN: (纸本)9781509016457

The image processing arose from the idea of the necessity to replace the human observer by a machine. The interest of this paper is to replace the medical image by information interpretable. Usually, experts have manually performed to count the cell nuclei biopsy samples, one by one. This method ensures that accuracy is achieved in the final diagnosis delivered by pathologists, but the time until the patient is notified can vary from weeks to months depending on the laboratory resources. Cancer developing speed is also a limiting factor, so the sooner the disease is discovered the better and quicker the patient can start with the treatment or preparations for surgery can be arranged. Promptness in cancer recognition increases the chances to overcome this illness that affects every year more and more men as the world population's life expectancy increases. So, for this reason, it has proposed an automatic method. To return the more reliable and fast diagnosis, we applied a method based on tools and algorithms. The chain of this processing is begun with the segmentation to separate the various constituent zones the image. Secondly, we have the step of detecting the edges of the prostatic cells as well their center. Finally, we have the step of counting where we are going to find a score for the diagnosis.

关键词： image processing segmentation detection of cells cancer counting of cells

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A Hybrid Algorithm for Dense Stereo Correspondences in Challenging Indoor Scenes

A Hybrid Algorithm for Dense Stereo Correspondences in Chall...

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IEEE International conference on Imaging systems and Techniques (IST) / IEEE International School on Imaging

作者： Georgousis, Stavros Stentoumis, Christos Doulamis, Nikolaos Voulodimos, Athanasios Natl Tech Univ Athens 9 Iroon Polytech Str GR-15773 Athens Greece

ISBN: (纸本)9781509018178

The algorithms for dense correspondences in stereo images are an extensively researched topic, since it is an essential step in a large number of applications. Despite the fact that the first stereo matching algorithms were proposed some decades ago, novel approaches regarding typical, but also cutting-edge applications, are always in demand. Stereo matching is an inverse, ill-posed problem, which usually depends on the application and the scenario. In this contribution, a hybrid approach for stereo matching is proposed, which is based on graph-cuts optimization (global) and cross-based aggregation (local) under a hierarchical scheme. It is shown that the combined effect of a global method in a coarse layer and a local method in finer layers improves the matching results. This hybrid approach exploits the strengths and ameliorates the weaknesses of the individual global and local algorithms. The resulted disparity map is robust without outliers even in untextured areas and at the same time high fidelity details are accurately represented. This hybrid scheme is evaluated on challenging indoor datasets. It is also computationally efficient for applying it on low-processing power applications.

关键词： stereo vision image matching image reconstruction pattern matching

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Depth Modeling Modes Complexity Control System for the 3D-HEVC Video Encoder

Depth Modeling Modes Complexity Control System for the 3D-HE...

引用

European Signal processing conference

作者： Gustavo Sanchez Mario Saldanha Luciano Agostini Cesar Marcon Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil IF Farroupilha Alegrete Brazil Federal University of Pelotas Pelotas Brazil

This paper presents a complexity control system for depth maps intra-frame prediction of the 3D-High Efficiency Video Coding (3D-HEVC) standard. The proposed system uses a Proportional-Integral-Derivative controller over the Simplified Edge Detector heuristic to skip the Depth Modeling Modes (DMMs) evaluation dynamically according to a defined target rate. When analyzing the proposed system under Common Test Conditions, the proposed controller stabilizes the system to the target rate (i.e., the percentage of DMMs evaluation) after encoding a few frames, with negligible encoding efficiency impacts. The BD-rate degradation varies from 0.50% to 0.20%, on average, when the target rates vary from 5% to 15%. These target rates imply in an aggressive reduction in the DMMs evaluations, skipping the DMMs from 85% to 95% of the cases.

关键词： Encoding Complexity theory Control systems image edge detection Signal processing algorithms Standards Three-dimensional displays

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The Development of Markov Random Field Theory and Applications on image Segmentation Algorithm

The Development of Markov Random Field Theory and Applicatio...

引用

International conference on Communication and Electronics systems (ICCES)

作者： Zhang, Renqian Huang, Yuru Fu, Sirui Fudan Univ Renqian Zhang Elect Engn Informat Dept Shanghai Peoples R China Beijing Univ Technol Beijing Peoples R China Lanzhou Univ Lanzhou Peoples R China

ISBN: (纸本)9781509010660

image segmentation algorithm is to divide the images into several regions with specific and unique characteristics, and is an important technology to extract the interested target. image segmentation is the key step to realize the research from general image processing into image analysis, and is vital preprocessing method of image recognition and computer vision. We cannot obtain correct recognition if we do not have correct segmentation. Nevertheless, the only basis of segmentation process is brightness or color of pixels in an image. In the processing of computer automatic segmentation, we experience several problems, such as uneven illumination, effect of noise, indistinct part in image, and shadow, and these factors may cause false segmentation. In order to overcome the disadvantages of the traditional segmentation algorithm, in this paper, we propose a novel segmentation algorithm based on Markov Random Field. The segmentation algorithm proposed in this paper is based on Markov Random Field Mode and Bayesian theory, and we determine the objective function in image segmentation problem on the basis of optimality criterion of statistical decision and estimation theory. Some optimization algorithms are used to obtain the maximum possible distribution of Markov Random Field which satisfy these conditions. The experimental result reflects the effectiveness and robustness of our algorithm. As a supplement, we analyze the development trend of the Markov Random Field theory.

关键词： Markov Random Field image segmentation Bayesian theory mathematical optimization algorithm design

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IVOVO: A new interval-valued one-vs-one approach for multi-class classification problems

IVOVO: A new interval-valued one-vs-one approach for multi-c...

引用

Joint World Congress of International Fuzzy systems Association and International conference on Soft Computing and Intelligent systems (IFSA-SCIS)

作者： Mikel Elkano Mikel Galar Jose Sanz Giancarlo Lucca Humberto Bustince Institute of Smart Cities Public University of Navarre Pamplona Spain

ISBN: (纸本)9781509049189

Decomposition strategies have been shown to be a successful methodology to tackle multi-class classification problems. Among them, One-vs-One approach is a commonly used technique that consists in dividing the original multi-class problem into easier-to-solve binary sub-problems considering each possible pair of classes. However, this methodology is limited to those classifiers returning a single real value for each prediction. In this work, we present a new One-vs-One approach that is able to deal with interval-valued outputs. In order to achieve this goal, we propose applying a normalization method for intervals along with the corresponding extension of three different aggregation strategies: voting, weighted voting, and WinWV. The experimental results show the suitability of the normalization method and the improvement obtained by One-vs-One with respect to a state-of-the-art interval-valued Fuzzy Rule-Based Classification System (IVTURS).

关键词： Pragmatics Training Fuzzy sets Signal to noise ratio image processing Classification algorithms Uncertainty

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Software Monitoring System for Register Marker Detection 8

Software Monitoring System for Register Marker Detection

引用

8th International conference on Ubiquitous and Future Networks (ICUFN)

作者： Kim, Sang-Chul Kookmin Univ Sch Comp Sci 77 Chongnung Ro Seoul 136702 South Korea

ISBN: (纸本)9781467399913

This paper proposes an image-processing algorithm for register marker detection in a roll-to-roll (R2R) system. Recently, R2R systems have been receiving considerable international attention from researchers because of their ability to print electronic devices on flexible substrates. During such printing, an R2R system must adjust its printing position by continuously checking the positions of the markers in order to ensure correct positioning of the printing roll. By acquiring the differences in the position information between referenced and printed marker positions, an R2R system can control the printing position by adjusting the printing roll speed. To capture and analyze referenced and printed marker images, an R2R system uses charge-coupled device (CCD) cameras and their image-processing algorithms. Therefore, it can be said that the productivity and accuracy of an R2R system depends entirely on the quality of the CCD cameras and their image-processing algorithms. This study develops an image-processing algorithm in which different markers are detected and processed.

关键词： Register Marker Detection Roll-to-Roll Software Imaging processing Software Monitoring System

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Colour Constancy Using Sub-Blocks of the image 9

Colour Constancy Using Sub-Blocks of the Image

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International conference on Signals and Electronic systems (ICSES)

作者： Hussain, Md. Akmol Akbari, Akbar Sheikh Mallik, Bruhanth Leeds Beckett Univ Sch Comp Creat Technol & Engn Leeds W Yorkshire England

ISBN: (纸本)9781509026678

Colour constancy is the ability to measure the colour of objects independent of the light source, while colour casting is the presence of unwanted colour in digital images. Colour casting significantly affects the performance of image processing algorithms such as image segmentation and object recognition. The presence of large uniform background within the image considerably deteriorates the performance of many state of the art colour constancy algorithms. This paper presents a colour constancy method using the sub-blocks of the image to alleviate the effect of large uniform colour area of the scene. The proposed method divides the input image into a number of nonoverlapping blocks, and Average Absolute Difference (AAD) value of each block colour component is calculated. The blocks with AAD greater than threshold values, which are empirically determined for each colour component, are considered to have sufficient colour information. The selected blocks are then used to determine the scaling factors to achieve achromatic values for the input image colour components. Comparing the performance of the proposed technique with the state of the art methods using images from three datasets shows that the proposed method outperforms the state of the art techniques in the presence of large uniform colour patches.

关键词： colour constancy colour balancing uniform colour average absolute difference

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