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Academic literature on the topic 'SIMULINK MODELS FOR VIDEO PROCESSING'

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Published: 11 September 2023

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Journal articles on the topic "SIMULINK MODELS FOR VIDEO PROCESSING"

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DOBLANDER, ANDREAS, DIETMAR GÖSSERINGER, BERNHARD RINNER, and HELMUT SCHWABACH. "AN EVALUATION OF MODEL-BASED SOFTWARE SYNTHESIS FROM SIMULINK MODELS FOR EMBEDDED VIDEO APPLICATIONS." International Journal of Software Engineering and Knowledge Engineering 15, no. 02 (April 2005): 343–48. http://dx.doi.org/10.1142/s0218194005002038.

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In next generation video surveillance systems there is a trend towards embedded solutions. Digital signal processors (DSP) are often used to provide the necessary computing power. The limited resources impose significant challenges for software development. Resource constraints must be met while facing increasing application complexity and pressing time-to-market demands. Recent advances in synthesis tools for Simulink suggest a high-level approach to algorithm implementation for embedded DSP systems. The model-based visual development process of Simulink facilitates simulation as well as synthesis of target specific code. In this work the modeling and code generation capabilities of Simulink are evaluated with respect to video analysis algorithms. Different models of a motion detection algorithm are used to synthesize code. The generated code targeted at a Texas Instruments TMS320C6416 DSP is compared to a hand-optimized reference. Experiments show that an ad hoc approach to synthesize complex image processing algorithms hardly yields optimal code for DSPs. However, several optimizations can be applied to improve performance.
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Naso, David, Olha Pohudina, Andrii Pohudin, Sergiy Yashin, and Rossella Bartolo. "Autonomous flight insurance method of unmanned aerial vehicles Parot Mambo using semantic segmentation data." Radioelectronic and Computer Systems, no. 1 (March 7, 2023): 147–54. http://dx.doi.org/10.32620/reks.2023.1.12.

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Autonomous navigation of unmanned aerial vehicles (UAVs) has become in the past decade an extremely attracting topic, also due to the increasing availability of affordable equipment and open-source control and processing software environments. This demand has also raised a strong interest in developing accessible experimental platforms to train engineering students in the rapidly evolving area of autonomous navigation. In this paper, we describe a platform based on low-cost off-the-shelf hardware that takes advantage of the Matlab/Simulink programming environment to tackle most of the problems related to UAV autonomous navigation. More specifically, the subject of this paper is the autonomous control of the flight of a small UAV, which must explore and patrol an indoor unknown environment. Objectives: to analyse the existing hardware platforms for autonomous flight indoors, choose a flight exploration scenario of unknown premises, to formalize the procedure for obtaining a model of knowledge for semantic classification of premises, to formalize obtaining distance to obstacles using data camera horizontally employment and building on its barrier map. Namely, we use the method of image segmentation based on the brightness threshold, a method of training the semantic segmentation network, and computer algorithms in probabilistic robotics for mobile robots. We consider both the case of navigation guided by structural visual information placed in the environment, e.g., contrast markers for flight (such as path marked by a red tape), and the case of navigation based on unstructured information such as recognizable objects or human gestures. Basing on preliminary tests, the most suitable method for autonomous in-door navigation is by using\ object classification and segmentation, so that the UAV gradually analyses the surrounding objects in the room and makes decisions on path planning. The result of our investigation is a method that is suitable to allow the autonomous flight of a UAV with a frontal video camera. Conclusions. The scientific novelty of the obtained results is as follows: we have improved the method of autonomous flight of small UAVs by using the semantic network model and determining the purpose of flight only at a given altitude to minimize the computational costs of limited autopilot capabilities for low-cost small UAV models. The results of our study can be further extended by means of a campaign of experiments in different environments.
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Coman, Mircea, and Balan Radu. "Video Camera Measuring Application Using Matlab." Solid State Phenomena 166-167 (September 2010): 139–44. http://dx.doi.org/10.4028/www.scientific.net/ssp.166-167.139.

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This paper presents the implementation in the Matlab/Simulink environment of an application for measuring distances using a video camera. Some of the advantages of using image processing as a method of measurement and of the Matlab for designing de application. The principles that where use to obtain de distance calculated where presented. Also the steps of the application implementation in Simulink where described.
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Bobyr, Maxim, Alexander Arkhipov, and Aleksey Yakushev. "Shade recognition of the color label based on the fuzzy clustering." Informatics and Automation 20, no. 2 (March 30, 2021): 407–34. http://dx.doi.org/10.15622/ia.2021.20.2.6.

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In this article the task of determining the current position of pneumatic actuators is considered. The solution to the given task is achieved by using a technical vision system that allows to apply the fuzzy clustering method to determine in real time the center coordinates and the displacement position of a color label located on the mechatronic complex actuators. The objective of this work is to improve the accuracy of the moving actuator’s of mechatronic complex by improving the accuracy of the color label recognition. The intellectualization of process of the color shade recognition is based on fuzzy clustering. First, a fuzzy model is built, that allows depending on the input parameters of the color intensity for each of the RGB channels and the color tone component, to select a certain color in the image. After that, the color image is binarized and noise is suppressed. The authors used two defuzzification models during simulation a fuzzy system: one is based on the center of gravity method (CoG) and the other is based on the method of area ratio (MAR). The model is implemented based on the method of area ratio and allows to remove the dead zones that are present in the center of gravity model. The method of area ratio determines the location of the color label in the image frame. Subsequently, when the actuator is moved longitudinally, the vision system determines the location of the color label in the new frame. The color label position offset between the source and target images allows to determine the moved distance of the color label. In order to study how noise affects recognition accuracy, the following digital filters were used: median, Gaussian, matrix and binomial. Analysis of the accuracy of these filters showed that the best result was obtained when using a Gaussian filter. The estimation was based on the signal-to-noise coefficient. The mathematical models of fuzzy clustering of color label recognition were simulated in the Matlab/Simulink environment. Experimental studies of technical vision system performance with the proposed fuzzy clustering model were carried out on a pneumatic mechatronic complex that performs processing, moving and storing of details. During the experiments, a color label was placed on the cylinder, after which the cylinder moved along the guides in the longitudinal direction. During the movement, video recording and image recognition were performed. To determine the accuracy of color label recognition, the PSNR and RMSE coefficients were calculated which were equal 38.21 and 3.14, respectively. The accuracy of determining the displacement based on the developed model for recognizing color labels was equal 99.7%. The defuzzifier speed has increased to 590 ns.
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Xie, Xiao Peng, and Yun Yi Li. "Computer Simulation Study Based on Matlab." Applied Mechanics and Materials 513-517 (February 2014): 3049–52. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3049.

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This paper describes the use of one of the Matlab toolbox dynamic simulation tool Simulink simulation methods, and improve simulation speed, the simulation results analysis conducted in-depth elaboration. Also describes the use of SIMULINK simulation tools to achieve automatic control system modeling, analysis and design, simulation methods and Simulink-based video and image processing module sets into visualization, modular modeling idea.
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Xin Li. "Video Processing Via Implicit and Mixture Motion Models." IEEE Transactions on Circuits and Systems for Video Technology 17, no. 8 (August 2007): 953–63. http://dx.doi.org/10.1109/tcsvt.2007.896656.

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Zhong, Zhaoqian, and Masato Edahiro. "Model-Based Parallelization for Simulink Models on Multicore CPUs and GPUs." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 20 (January 4, 2020): 1–13. http://dx.doi.org/10.24297/ijct.v20i.8533.

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In this paper we propose a model-based approach to parallelize Simulink models of image processing algorithms on homogeneous multicore CPUs and NVIDIA GPUs at the block level and generate CUDA C codes for parallel execution on the target hardware. In the proposed approach, the Simulink models are converted to directed acyclic graphs (DAGs) based on their block diagrams, wherein the nodes represent tasks of grouped blocks or subsystems in the model and the edges represent the communication behaviors between blocks. Next, a path analysis is conducted on the DAGs to extract all execution paths and calculate their respective lengths, which comprises the execution times of tasks and the communication times of edges on the path. Then, an integer linear programming (ILP) formulation is used to minimize the length of the critical path of the DAG, which represents the execution time of the Simulink model. The ILP formulation also balances workloads on each CPU core for optimized hardware utilization. We parallelized image processing models on a platform of two homogeneous CPU cores and two GPUs with our approach and observed a speedup performance between 8.78x and 15.71x.
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Arsinte, Radu, and Eugen Lupu. "Prototyping Industrial Vision Applications and Implementations on Multimedia Processors." Applied Mechanics and Materials 808 (November 2015): 321–26. http://dx.doi.org/10.4028/www.scientific.net/amm.808.321.

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The article presents a development system for industrial vision applications based on multimedia processors. For simulation of the algorithm and prototyping the application we can use either standard Matlab / Simulink environment or specialized environments such as Open eVision. The system components are presented with examples of application prototyping and implementation on standard platform Digital Video Development Platform DVDP6437 from Spectrum Digital, equipped with Texas Instruments TMS320DM6437. In the presented system we did experiments regarding the Rapid Prototyping concept in industrial vision application, starting from Embedded Target Library components from Matlab / Simulink. The experiments revealed that multimedia processors are usable both in video and still image processing and are possible to be considered an option in standard industrial vision applications: positioning, visual inspection. The paper contains also a brief study of the necessary components of a proposed embedded architecture, intended to be realized for evaluation of the technology in industrial environments.
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Hanh, Le Thi My, Nguyen Thanh Binh, and Khuat Thanh Tung. "Parallel Mutant Execution Techniques in Mutation Testing Process for Simulink Models." Journal of Telecommunications and Information Technology 4 (December 20, 2017): 90–100. http://dx.doi.org/10.26636/jtit.2017.113617.

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Mutation testing – a fault-based technique for software testing – is a computationally expensive approach. One of the powerful methods to improve the performance of mutation without reducing effectiveness is to employ parallel processing, where mutants and tests are executed in parallel. This approach reduces the total time needed to accomplish the mutation analysis. This paper proposes three strategies for parallel execution of mutants on multicore machines using the Parallel Computing Toolbox (PCT) with the Matlab Distributed Computing Server. It aims to demonstrate that the computationally intensive software testing schemes, such as mutation, can be facilitated by using parallel processing. The experiments were carried out on eight different Simulink models. The results represented the efficiency of the proposed approaches in terms of execution time during the testing process.
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Maqsood, Azka, Imran Touqir, Adil Masood Siddiqui, and Maham Haider. "Wavelet Based Video Denoising using Probabilistic Models." January 2019 38, no. 1 (January 1, 2019): 17–30. http://dx.doi.org/10.22581/muet1982.1901.02.

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Wavelet based image processing techniques do not strictly follow the conventional probabilistic models that are unrealistic for real world images. However, the key features of joint probability distributions of wavelet coefficients are well captured by HMT (Hidden Markov Tree) model. This paper presents the HMT model based technique consisting of Wavelet based Multiresolution analysis to enhance the results in image processing applications such as compression, classification and denoising. The proposed technique is applied to colored video sequences by implementing the algorithm on each video frame independently. A 2D (Two Dimensional) DWT (Discrete Wavelet Transform) is used which is implemented on popular HMT model used in the framework of Expectation-Maximization algorithm. The proposed technique can properly exploit the temporal dependencies of wavelet coefficients and their non-Gaussian performance as opposed to existing wavelet based denoising techniques which consider the wavelet coefficients to be jointly Gaussian or independent. Denoised frames are obtained by processing the wavelet coefficients inversely. Comparison of proposed method with the existing techniques based on CPSNR (Coloured Peak Signal to Noise Ratio), PCC (Pearson’s Correlation Coefficient) and MSSIM (Mean Structural Similarity Index) has been carried out in detail.The proposed denoising method reveals improved results in terms of quantitative and qualitative analysis for both additive and multiplicative noise and retains nearly all the structural contents of a video frame.
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Dissertations / Theses on the topic "SIMULINK MODELS FOR VIDEO PROCESSING"

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Monaco, Joseph W. "Generalized motion models for video applications." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/14926.

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Owen, Michael Information Technology &amp Electrical Engineering Australian Defence Force Academy UNSW. "Temporal motion models for video mosaicing and synthesis." Awarded by:University of New South Wales - Australian Defence Force Academy, 2008. http://handle.unsw.edu.au/1959.4/39028.

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Video compression aims to reduce video file size without impacting visual quality. Existing algorithms mostly use transform coders to convert information from the spatial to frequency domain, and attenuate or remove high frequency components from the sequence. This enables the omission of a large proportion of high frequency information with no discernible visual impact. Sprite-based compression encodes large portions of a scene as a single object in the video sequence, recreating the object in subsequent frames by warping or morphing the sprite to mimic changes in subsequent frames. This thesis sought to improve several aspects of existing sprite based compression approaches, employing a temporal motion model using a low order polynomial to represent the motion of an object across multiple frames in a single model rather than a series of models. The main outcome is the demonstration that motion models used by sprite based video compression can be extended to a full three dimensional model, reducing the overall size of the model, and improving the quality of the sequence at low bit rates. A second outcome is the demonstration that super-resolution processing is not necessary if lanczos spatial interpolation is used instead of bilinear or bi-cubic interpolation, resulting in a savings in computational time and resources. A third outcome is the introduction of a new blending model used to generate image mosaics that improves the quality of the synthesised sequence when zoom is present in the sequence for a given bit-rate. A final outcome is demonstrating that performing superresolution processing and sub-sampling back to the original resolution prior to compression provides benefits in some circumstances.
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Jónsson, Ragner H. "Adaptive subband coding of video using probability distribution models." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/14453.

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Zapata, Iván R. "Detecting humans in video sequences using statistical color and shape models." [Gainesville, Fla.] : University of Florida, 2001. http://etd.fcla.edu/etd/uf/2001/anp1058/ivan%5Fthesis2.pdf.

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Thesis (M.S.)--University of Florida, 2001.
Title from first page of PDF file. Document formatted into pages; contains viii, 49 p.; also contains graphics. Vita. Includes bibliographical references (p. 47-48).
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FOTIO, TIOTSOP LOHIC. "Optimizing Perceptual Quality Prediction Models for Multimedia Processing Systems." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2970982.

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Lee, Sangkeun. "Video analysis and abstraction in the compressed domain." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04072004-180041/unrestricted/lee%5fsangkeun%5f200312%5fphd.pdf.

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Lazcano, Vanel. "Some problems in depth enhanced video processing." Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/373917.

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In this thesis we tackle two problems, namely, the data interpolation prob- lem in the context of depth computation both for images and for videos, and the problem of the estimation of the apparent movement of objects in image sequences. The rst problem deals with completion of depth data in a region of an image or video where data are missing due to occlusions, unreliable data, damage or lost of data during acquisition. In this thesis we tackle it in two ways. First, we propose a non-local gradient-based energy which is able to complete planes locally. We consider this model as an extension of the bilateral lter to the gradient domain. We have successfully evaluated our model to complete synthetic depth images and also incomplete depth maps provided by a Kinect sensor. The second approach to tackle the problem is an experimental study of the Biased Absolutely Minimizing Lipschitz Extension (biased AMLE in short) for anisotropic interpolation of depth data to big empty regions without informa- tion. The AMLE operator is a cone interpolator, but the biased AMLE is an exponential cone interpolator which makes it more addapted to depth maps of real scenes that usually present soft convex or concave surfaces. Moreover, the biased AMLE operator is able to expand depth data to huge regions. By con- sidering the image domain endowed with an anisotropic metric, the proposed method is able to take into account the underlying geometric information in order not to interpolate across the boundary of objects at di erent depths. We have proposed a numerical model to compute the solution of the biased AMLE which is based on the eikonal operators. Additionally, we have extended the proposed numerical model to video sequences. The second problem deals with the motion estimation of the objects in a video sequence. This problem is known as the optical ow computation. The Optical ow problem is one of the most challenging problems in computer vision. Traditional models to estimate it fail in presence of occlusions and non-uniform illumination. To tackle these problems we proposed a variational model to jointly estimate optical ow and occlusion. Moreover, the proposed model is able to deal with the usual drawback of variational methods in dealing with fast displacements of objects in the scene which are larger than the object it- self. The addition of a term that balance gradient and intensities increases the robustness to illumination changes of the proposed model. The inclusions of a supplementary matches given by exhaustive search in speci cs locations helps to follow large displacements.
En esta tesis se abordan dos problemas: interpolación de datos en el contexto del cálculo de disparidades tanto para imágenes como para video, y el problema de la estimación del movimiento aparente de objetos en una secuencia de imágenes. El primer problema trata de la completación de datos de profundidad en una región de la imagen o video dónde los datos se han perdido debido a oclusiones, datos no confiables, datos dañados o pérdida de datos durante la adquisición. En esta tesis estos problemas se abordan de dos maneras. Primero, se propone una energía basada en gradientes no-locales, energía que puede (localmente) completar planos. Se considera este modelo como una extensión del filtro bilateral al dominio del gradiente. Se ha evaluado en forma exitosa el modelo para completar datos sintéticos y también mapas de profundidad incompletos de un sensor Kinect. El segundo enfoque, para abordar el problema, es un estudio experimental del biased AMLE (Biased Absolutely Minimizing Lipschitz Extension) para interpolación anisotrópica de datos de profundidad en grandes regiones sin información. El operador AMLE es un interpolador de conos, pero el operador biased AMLE es un interpolador de conos exponenciales lo que lo hace estar más adaptado a mapas de profundidad de escenas reales (las que comunmente presentan superficies convexas, concavas y suaves). Además, el operador biased AMLE puede expandir datos de profundidad a regiones grandes. Considerando al dominio de la imagen dotado de una métrica anisotrópica, el método propuesto puede tomar en cuenta información geométrica subyacente para no interpolar a través de los límites de los objetos a diferentes profundidades. Se ha propuesto un modelo numérico, basado en el operador eikonal, para calcular la solución del biased AMLE. Adicionalmente, se ha extendido el modelo numérico a sequencias de video. El cálculo del flujo óptico es uno de los problemas más desafiantes para la visión por computador. Los modelos tradicionales fallan al estimar el flujo óptico en presencia de oclusiones o iluminación no uniforme. Para abordar este problema se propone un modelo variacional para conjuntamente estimar flujo óptico y oclusiones. Además, el modelo propuesto puede tolerar, una limitación tradicional de los métodos variacionales, desplazamientos rápidos de objetos que son más grandes que el tamaño objeto en la escena. La adición de un término para el balance de gradientes e intensidades aumenta la robustez del modelo propuesto ante cambios de iluminación. La inclusión de correspondencias adicionales (obtenidas usando búsqueda exhaustiva en ubicaciones específicas) ayuda a estimar grandes desplazamientos.
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Hautala, I. (Ilkka). "From dataflow models to energy efficient application specific processors." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526223681.

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Abstract The development of wireless networks has provided the necessary conditions for several new applications. The emergence of the virtual and augmented reality and the Internet of things and during the era of social media and streaming services, various demands related to functionality and performance have been set for mobile and wearable devices. Meeting these demands is complicated due to minimal energy budgets, which are characteristic of embedded devices. Lately, the energy efficiency of devices has been addressed by increasing parallelism and the use of application-specific hardware resources. This has been hindered by hardware development as well as software development because the conventional development methods are based on the use of low-level abstractions and sequential programming paradigms. On the other hand, deployment of high-level design methods is slowed down because of final solutions that are too much compromised when energy efficiency and performance are considered. This doctoral thesis introduces a model-driven framework for the development of signal processing systems that facilitates hardware and software co-design. The design flow exploits an easily customizable, re-programmable and energy-efficient processor template. The proposed design flow enables tailoring of multiple heterogeneous processing elements and the connections between them to the demands of an application. Application software is described by using high-level dataflow models, which enable the automatic synthesis of parallel applications for different multicore hardware platforms and speed up design space exploration. Suitability of the proposed design flow is demonstrated by using three different applications from different signal processing domains. The experiments showed that raising the level of abstraction has only a minor impact on performance. Video processing algorithms are selected to be the main application area in this thesis. The thesis proposes tailored and reprogrammable energy-efficient processing elements for video coding algorithms. The solutions are based on the use of multiple processing elements by exploiting the pipeline parallelism of the application, which is characteristic of many signal processing algorithms. Performance, power and area metrics for the designed solutions have been obtained using post-layout simulation models. In terms of energy efficiency, the proposed programmable processors form a new compromise solution between fixed hardware accelerators and conventional embedded processors for video coding
Tiivistelmä Langattomien verkkojen kehittyminen on luonut edellytykset useille uusille sovelluksille. Muiden muassa sosiaalisen media, suoratoistopalvelut, virtuaalitodellisuus ja esineiden internet asettavat kannettaville ja puettaville laitteille moninaisia toimintoihin, suorituskykyyn, energiankulutukseen ja fyysiseen muotoon liittyviä vaatimuksia. Yksi isoimmista haasteista on sulautettujen laitteiden energiankulutus. Laitteiden energiatehokkuutta on pyritty parantamaan rinnakkaislaskentaa ja räätälöityjä laskentaresursseja hyödyntämällä. Tämä puolestaan on vaikeuttanut niin laite- kuin sovelluskehitystä, koska laajassa käytössä olevat kehitystyökalut perustuvat matalan tason abstraktioihin ja hyödyntävät alun perin yksi ydinprosessoreille suunniteltuja ohjelmointikieliä. Korkean tason ja automatisoitujen kehitysmenetelmien käyttöönottoa on hidastanut aikaansaatujen järjestelmien puutteellinen suorituskyky ja laiteresurssien tehoton hyödyntäminen. Väitöskirja esittelee datavuopohjaiseen suunnitteluun perustuvan työkaluketjun, joka on tarkoitettu energiatehokkaiden signaalikäsittelyjärjestelmien toteuttamiseen. Työssä esiteltävä suunnitteluvuo pohjautuu laitteistoratkaisuissa räätälöitävään ja ohjelmoitavaan siirtoliipaistavaan prosessoritemplaattiin. Ehdotettu suunnitteluvuo mahdollistaa useiden heterogeenisten prosessoriytimien ja niiden välisten kytkentöjen räätälöimisen sovelluksien tarpeiden vaatimalla tavalla. Suunnitteluvuossa ohjelmistot kuvataan korkean tason datavuomallien avulla. Tämä mahdollistaa erityisesti rinnakkaista laskentaa sisältävän ohjelmiston automaattisen sovittamisen erilaisiin moniprosessorijärjestelmiin ja nopeuttaa erilaisten järjestelmätason ratkaisujen kartoittamista. Suunnitteluvuon käyttökelpoisuus osoitetaan käyttäen esimerkkinä kolmea eri signaalinkäsittelysovellusta. Tulokset osoittavat, että suunnittelumenetelmien abstraktiotasoa on mahdollista nostaa ilman merkittävää suorituskyvyn heikkenemistä. Väitöskirjan keskeinen sovellusalue on videonkoodaus. Työ esittelee videonkoodaukseen suunniteltuja energiatehokkaita ja uudelleenohjelmoitavia prosessoriytimiä. Ratkaisut perustuvat usean prosessoriytimen käyttämiseen hyödyntäen erityisesti videonkäsittelyalgoritmeille ominaista liukuhihnarinnakkaisuutta. Prosessorien virrankulutus, suorituskyky ja pinta-ala on analysoitu käyttämällä simulointimalleja, jotka huomioivat logiikkasolujen sijoittelun ja johdotuksen. Ehdotetut sovelluskohtaiset prosessoriratkaisut tarjoavat uuden energiatehokkaan kompromissiratkaisun tavanomaisten ohjelmoitavien prosessoreiden ja kiinteästi johdotettujen video-kiihdyttimien välille
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KABRA, PRATEEK. "IMPLEMENTATION OF REAL TIME OBJECT DETECTION & TRACKING." Thesis, 2012. http://dspace.dtu.ac.in:8080/jspui/handle/repository/13908.

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M.TECH
In this project we present an approach to develop a real-time object tracking system using a static camera to grab the video frames and track an object. The work presents the concepts of histogram matching and absolute frame subtraction to implement a robust automated object tracking system. Once the object is detected it is tracked using discrete Kalman filter technique. The histogram matching algorithm helps to identify when the object enters the viewing range of the camera and the absolute frame subtraction gives better results even with low quality videos. Such a tracking system can be used in surveillance applications and proves to be cost effective. A simulink model is also developed for object tracking for real time video
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"Markov random fields based image and video processing." Thesis, 2010. http://library.cuhk.edu.hk/record=b6074890.

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In this dissertation, we propose three methods to solve the problems of interactive image segmentation, video completion, and image denoising, which are all formulated as MRF-based energy minimization problems. In our algorithms, different MRF-based energy functions with particular techniques according to the characteristics of different tasks are designed to well fit the problems. With the energy functions, different optimization schemes are proposed to find the optimal results in these applications. In interactive image segmentation, an iterative optimization based framework is proposed, where in each iteration an MRF-based energy function incorporating an estimated initial probabilistic map of the image is optimized with a relaxed global optimal solution. In video completion, a well-defined MRF energy function involving both spatial and temporal coherence relationship is constructed based on the local motions calculated in the first step of the algorithm. A hierarchical belief propagation optimization scheme is proposed to efficiently solve the problem. In image denoising, label relaxation based optimization on a Gaussian MRF energy is used to achieve the global optimal closed form solution.
Many problems in computer vision involve assigning each pixel a label, which represents some spatially varying quantity such as image intensity in image denoising or object index label in image segmentation. In general, such quantities in image processing tend to be spatially piecewise smooth, since they vary smoothly in the object surface and change dramatically at object boundaries, while in video processing, additional temporal smoothness is satisfied as the corresponding pixels in different frames should have similar labels. Markov random field (MRF) models provide a robust and unified framework for many image and video applications. The framework can be elegantly expressed as an MRF-based energy minimization problem, where two penalty terms are defined with different forms. Many approaches have been proposed to solve the MRF-based energy optimization problem, such as simulated annealing, iterated conditional modes, graph cuts, and belief propagation.
Promising results obtained by the proposed algorithms, with both quantitative and qualitative comparisons to the state-of-the-art methods, demonstrate the effectiveness of our algorithms in these image and video processing applications.
Liu, Ming.
Adviser: Xiaoou Tang.
Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: .
Thesis (Ph.D.)--Chinese University of Hong Kong, 2010.
Includes bibliographical references (leaves 79-89).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract also in Chinese.
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Books on the topic "SIMULINK MODELS FOR VIDEO PROCESSING"

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van den Branden Lambrecht, Christian J., ed. Vision Models and Applications to Image and Video Processing. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3411-9.

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Branden Lambrecht, Christian J. van den., ed. Vision models and applications to image and video processing. Boston: Kluwer Academic, 2001.

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Lambrecht, Christian J. Branden. Vision Models and Applications to Image and Video Processing. Boston, MA: Springer US, 2001.

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Binh, Le Nguyen. Nonlinear optical systems: Principles, applications, and advanced signal processing with MATLAB and simulink models. Boca Raton: Taylor & Francis, 2012.

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Katsaggelos, Aggelos Konstantinos. Super resolution of images and video. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool Publishers, 2007.

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Microcomputer spreadsheet models for libraries: Preparing documents, budgets, and statistical reports. Chicago: American Library Association, 1985.

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Winkler, Stefan. Digital Video Quality: Vision Models and Metrics. Wiley & Sons, Incorporated, John, 2013.

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Winkler, Stefan. Digital Video Quality: Vision Models and Metrics. Wiley & Sons, Incorporated, John, 2007.

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Digital Video Quality: Vision Models and Metrics. Wiley, 2005.

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Winkler, Stefan. Digital Video Quality: Vision Models and Metrics. Wiley & Sons, Limited, John, 2013.

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Book chapters on the topic "SIMULINK MODELS FOR VIDEO PROCESSING"

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Delakis, Manolis, Guillaume Gravier, and Patrick Gros. "Stochastic Models for Multimodal Video Analysis." In Multimodal Processing and Interaction, 1–19. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-76316-3_3.

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Wu, Xiaoyu, Yangsheng Wang, and Jituo Li. "Video Background Segmentation Using Adaptive Background Models." In Image Analysis and Processing – ICIAP 2009, 623–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04146-4_67.

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Winkler, Stefan, Murat Kunt, and Christian J. van den Branden Lambrecht. "Vision and Video: Models and Applications." In Vision Models and Applications to Image and Video Processing, 201–29. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3411-9_10.

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Meilhac, Christophe, and Chahab Nastar. "Robust fitting of 3D CAD models to video streams." In Image Analysis and Processing, 661–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63507-6_258.

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Gong, Shengrong, Chunping Liu, Yi Ji, Baojiang Zhong, Yonggang Li, and Husheng Dong. "Dynamic Scene Classification Based on Topic Models." In Advanced Image and Video Processing Using MATLAB, 429–74. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77223-3_12.

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Taskiran, Cuneyt M., Ilya Pollak, Charles A. Bouman, and Edward J. Delp. "Stochastic Models of Video Structure for Program Genre Detection." In Visual Content Processing and Representation, 84–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39798-4_13.

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Falcon, Alex, Giuseppe Serra, and Oswald Lanz. "Learning Video Retrieval Models with Relevance-Aware Online Mining." In Image Analysis and Processing – ICIAP 2022, 182–94. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06433-3_16.

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Ledda, Emanuele, Lorenzo Putzu, Rita Delussu, Giorgio Fumera, and Fabio Roli. "On the Evaluation of Video-Based Crowd Counting Models." In Image Analysis and Processing – ICIAP 2022, 301–11. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06433-3_26.

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Daly, Scott. "Engineering Observations from Spatiovelocity and Spatiotemporal Visual Models." In Vision Models and Applications to Image and Video Processing, 179–200. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3411-9_9.

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Mrak, Marta, and Toni Zgaljic. "Flexible Motion Models for Scalable and High Definition Video Coding." In Recent Advances in Multimedia Signal Processing and Communications, 209–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02900-4_9.

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Conference papers on the topic "SIMULINK MODELS FOR VIDEO PROCESSING"

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Kanayama, Ai, and Tomonori Tabusa. "Auto-capturing system for facial images from video by Simulink model." In 2010 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS 2010). IEEE, 2010. http://dx.doi.org/10.1109/ispacs.2010.5704635.

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Ostroumov, Sergey, Pontus Bostrom, and Marina Walden. "Derivation of Parallel and Resilient Programs from Simulink Models." In 2015 23rd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP). IEEE, 2015. http://dx.doi.org/10.1109/pdp.2015.102.

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Ayed, Tahar, Adnane Cabani, and Joseph Mouzna. "Performance of Video Reception on T-DMB Embedded Receivers using Simulink Modeling." In Signal and Image Processing and Applications / Artificial Intelligence and Soft Computing. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.738-050.

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Liu, Yuhua, Wei Zhou, Hongcheng Li, and Chenfu Yi. "Time-invariant Lyapunov matrix equation solving by Neural Networks with Simulink models." In 2014 12th International Conference on Signal Processing (ICSP 2014). IEEE, 2014. http://dx.doi.org/10.1109/icosp.2014.7015252.

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Hai, Jerry Chan Ting, Ooi Chee Pun, and Tan Wooi Haw. "Accelerating video and image processing design for FPGA using HDL coder and simulink." In 2015 IEEE Conference on Sustainable Utilization And Development In Engineering and Technology (CSUDET). IEEE, 2015. http://dx.doi.org/10.1109/csudet.2015.7446221.

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Bosch, Marc, Fengqing Zhu, and Edward J. Delp. "Spatial Texture Models for Video Compression." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4378899.

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Butt, Shahzad Ahmad, and Luciano Lavagno. "Design space exploration and synthesis for digital signal processing algorithms from Simulink models." In 2013 Design and Test Symposium (IDT). IEEE, 2013. http://dx.doi.org/10.1109/idt.2013.6727109.

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Toreyin, B. U., Y. Dedeoglu, and A. E. Cetin. "Flame detection in video using hidden Markov models." In rnational Conference on Image Processing. IEEE, 2005. http://dx.doi.org/10.1109/icip.2005.1530284.

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Ding, Yi, and Laiyao Fan. "Object-oriented video structuring via hidden Markov models." In Visual Communications and Image Processing 2005. SPIE, 2005. http://dx.doi.org/10.1117/12.631558.

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Barman, Nabajeet, Rahul Vanam, and Yuriy Reznik. "Parametric Quality Models for Multiscreen Video Systems." In 2022 10th European Workshop on Visual Information Processing (EUVIP). IEEE, 2022. http://dx.doi.org/10.1109/euvip53989.2022.9922693.

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