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GPU-accelerated feature tracking

GPU-accelerated feature tracking

引用

IEEE National conference on Aerospace and Electronics (NAECON)

作者： Alexander Graves University of Dayton Research Institute Dayton USA

ISBN: (纸本)9781509034420

The motivation of this research is to prove that Graphics processing Units (GPUs) can provide significant speedup of long-executing image processing algorithms by way of parallelization and data throughput. This research accelerates the Kanade-Lucas-Tomasi (KLT) feature tracking algorithm using OpenCL. KLT can easily suffer from low frame rates when tracking many features in a video sequence. The experiments conducted prove that when tracking over 500 features in a high definition (HD) dataset, GPU-based KLT provides a 92% reduction in total runtime compared to a CPU-based implementation.

关键词： Programming Algorithm design and analysis image processing Convolution Graphics processing units High definition video signal processing algorithms

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Systematic design of object shape matched wavelet filter banks for defect detection

Systematic design of object shape matched wavelet filter ban...

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International conference on Telecommunications and signal processing (TSP)

作者： Tan-Toan Le Mathias Ziebarth Thomas Greiner Michael Heizmann Institute of Smart Systems and Services Pforzheim University Pforzheim Germany Institute for Anthropomatics Karlsruhe Institute of Technology Karlsruhe Germany Fraunhofer IOSB Karlsruhe Germany

ISBN: (纸本)9781509012893

In our previous works, we have presented methods for optimizing wavelet filter banks, which can be used for classification of image objects. The wavelet filter banks were designed to be biorthogonal, which enables a multiscale analysis on given image data. Moreover, the filters were optimized with respect to the shape, which helps the filter banks to inherit the property of the objects. This optimization is only possible with the help of so called object filters designed to have the curve of typical objects of each class. In contrast to previous works where object filters were designed manually, a systematic and automatic design method for object filters is introduced in this paper. The new designed filters were used to optimize wavelet filter banks for classification problems. The evaluation of this method was done by comparing the results with the ones of wavelet filter banks based on the previously used object filters.

关键词： Shape Wavelet transforms Wavelet analysis Hafnium Cameras Surface reconstruction

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design and Implementation of image processing Algorithms for Cardiac Blockage Detection on FPGA

Design and Implementation of Image Processing Algorithms for...

引用

IEEE Annual India conference

作者： Shrinivas B Mudigoudar Abdul Imran Rasheed Electronic and Communication Engineering Department M. S. Ramaiah University of Applied Sciences Bengaluru India

ISBN: (纸本)9781509036479

Nowadays, major health issues are concerned with heart problems say, heart attack. The main cause for heart attack is plaque. The Cardiac Plaque is waxy substance buildup inside the coronary arteries. Plaque results blockages inside the coronary arteries. The cardiac angiogram or cardiac catheterization is an approach used for the diagnosis of coronary blockages. It is an expensive and invasive approach to detect cardiac blockages. So, the angiogram is a conventional approach to diagnose cardiac blockages. In this paper, cardiac blockages are detected by means of Canny edge detector and Watershed image processing algorithms implemented on FPGA (Hardware implementation). The proposed design consumes power of 118 mW and maximum operating frequency is 338.295 MHz and minimum period is 2.956 ns.

关键词： Angiogram CABG (Coronary Artery Bypass Surgery) Catheterization Plaque PSNR (Peak signal to Noise Ratio)

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A nearly lossless compression system for Bayer pattern images of a capsule endoscopy

A nearly lossless compression system for Bayer pattern image...

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International conference on signal processing and Communication Systems, ICSPCS

作者： Qasim Al-Shebani Prashan Premaratne Peter James Vial School of Electrical and Computer and Telecommunications Engineering University of Wollongong North Wollongong NSW Australia

ISBN: (纸本)9781509009428

image Compression is very important tool to reduce the complexity and the power consumption for applications that have limited size capacity such as capsule endoscopy. To reduce the power required to code and transmite the resulting data of the capsule images, research has mainly focused on reducing the complexity of the design of image compression system. This was either by utlizing interpolation technique to convert the resulting Bayer images into full colour images or by modifing colour transformation with structure conversion to dedicate the Bayer images to the available image compression systems. Both methods are in high power consumption, requiring long processing time and on-chip memory. Thus, this study aims to develop a nearly lossless image compression system with a novel method of subtraction schemefollowed by a linear prediction and Golomb-Rice. The results of this study shows an excellent compression ratio of 93% and high quality reconstructed images with PSNR of 42dB. These results and the high mean structure similarity index matching between the original and the decompressed images confirm the validity of the proposed image compression system. Since this new method has overcome the need for either colour transformation or structure separation units which were necessary units in the compression systems for capsule endoscopy in the existing literature, the power and the processing time which was required to run those units has been eliminated by our new method.

关键词： image coding image color analysis Endoscopes image reconstruction Power demand Interpolation Memory management

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Asic design of low power VLSI architecture for different multiplier algorithms using compressors

Asic design of low power VLSI architecture for different mul...

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International conference on Industrial and Information Systems, ICIIS

作者： R. Abhilash Sanjay Dubey M. C. Chinnaaiah Department of ECE BVRIT Telangana India

In most of the digital systems, adders and multipliers are the fundamental components in the design of many applications domains such as a digital signal processing especially for multimedia application such as graphics 3D depends on extensive number of multiplication, scientific and numerical applications. This paper proposes a novel Compressors for low power VLSI architecture of different multiplier Algorithms and their ASIC design. Purely combinational logic is used in the design of these multipliers. The partial product bits are obtained by ANDing of both multiplier and multiplicand bit. Then the partial Products are summed using compressor technique. In this paper the proposed novel 4-2 and 5-2 compressors architecture achieve low energy consumption, when used for different multipliers. All the proposed architectures are designed using Verilog HDL and are simulated using Xilinx tool for functionality verification. The physical verification is also done using the 180nm tsmc technology library, operating in slow (balanced-tree) conditions generated by Encounter (R) compiler. In particular, the results were compared with conventional multiplier algorithms and found that the proposed compressors when used in multiplier algorithms are more efficient in terms of power.

关键词： Compressors Logic gates Adders Algorithm design and analysis signal processing algorithms Multiplexing Power demand

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The Study Analysis Knee Angle of Color Set Detection Using image processing Technique

The Study Analysis Knee Angle of Color Set Detection Using I...

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International IEEE conference on signal-image Technologies and Internet-Based System

作者： Patiyuth Pramkeaw Department of Media Technology King Mongkut's University of Technology Thonburi Bangkok Thailand

This research aimed to the study analysis knee angle of color set detection using image processing technique. It had been developed to assist the patient after knee joint surgery or those who had knee joint problem by detecting value from color set to record result for treatment planning and shortening time to diagnose or set knee joint treatment planning for physician. This research utilized the video camera to record the knee joint therapy and displayed the color detection real-time result on computer. Connected-component labeling and bounding box techniques using Open CV program to design color detector from color set software which displayed the current angle and recorded the patient data as the new patient and existing patient. Results from three patients showed that the analysis system of knee joint angle was useable. The accuracy of program was 96% and the system could record the patient data as new and existing patient. Moreover, the system could be applied to analyze the condition or treatment planning for the physician.

关键词： Knee image color analysis Medical treatment Joints Planning

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Scalable EEG seizure detection on an ultra low power multi-core architecture

Scalable EEG seizure detection on an ultra low power multi-c...

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IEEE Biomedical Circuits and Systems (BIOCAS)

作者： S. Benatti F. Montagna D. Rossi L. Benini DEI University of Bologna Italy ETHZ Integrated System Laboratory Zurich Switzerland

ISBN: (纸本)9781509029600

Energy efficient processing architectures represent key elements for wearable and implantable medical devices. signal processing of neural data is a challenge in new designs of Brain Machine Interfaces (BMI). A highly efficient multi-core platform, designed for ultra low power processing allows the execution of complex algorithms complying with real time requirements. This paper describes the implementation and optimization of a seizure detection algorithm on a multi-core digital integrated circuit designed for energy efficient applications. The proposed architecture is able to implement ultra low power parallel processing seizure detection on 23 electrodes within a power budget of 1 mW, outperforming implementations on commercial MCUs by up to 100 times in terms of performance and up to 80 times in terms of energy efficiency still providing high versatility and scalability, opening the way to the development of efficient implantable and wearable smart systems.

关键词： Electroencephalography Computer architecture Kernel Support vector machines signal processing algorithms Algorithm design and analysis Electrodes

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soft-NEON: A study on replacing the NEON engine of an ARM SoC with a reconfigurable fabric

soft-NEON: A study on replacing the NEON engine of an ARM So...

引用

International conference on Application Specific Systems (ASAP), architectures and Processors

作者： Jose Raul Garcia Ordaz Dirk Koch School of Computer science The University of Manchester Manchester United Kingdom

ISBN: (纸本)9781509015047

Power is a limiting factor in the design of embedded processors. For this reason adding more instruction extensions is not a scalable option. To overcome this issue, we study the effects of replacing the NEON unit of an ARM SoC with an FPGA-like reconfigurable fabric. We measure the gap between the conventional hard-NEON and a soft-NEON implementation. We found that the soft-NEON has an overhead of 25.17× and 6.23× for area and latency, respectively. This overhead is reduced by exploiting the reconfigurability of the fabric by incorporating FPGA-specific optimization techniques. Moreover, we show that instead of implementing the pre-defined NEON instruction set, custom instructions can be loaded to the reconfigurable fabric by using a HLS compilation flow. With this approach performance gains of over 2.8× have been obtained for some kernels.

关键词： Neon Fabrics Table lookup Digital signal processing Field programmable gate arrays Kernel Benchmark testing

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RRAM based Learning acceleration

RRAM based Learning acceleration

引用

Proceedings of the International conference on Compilers, architectures and Synthesis for Embedded Systems (CASES)

作者： Yu Wang Lixue Xia Ming Cheng Tianqi Tang Boxun Li Huazhong Yang Dept. of E.E. Tsinghua University Beijing China Tsinghua University Beijing Beijing CN

ISBN: (纸本)9781509035892

Deep Learning (DL) is becoming popular in a wide range of domains. Many emerging applications, ranging from image and speech recognition to natural language processing and information retrieval, rely heavily on deep learning techniques, especially the Neural Networks (NNs). NNs have led to great advances in recognition accuracy compared with other traditional methods in recent years. NN-based methods demand much more computation and memory resource, and therefore a number of NN accelerators have been proposed on CMOS-based platforms, such as FPGA and GPU [1]. However, it becomes more and more difficult to obtain substantial power efficiency and gains directly through the scaling down of traditional CMOS technique. Meanwhile, the large data amount in DL applications also meets an ever-increasing “memory wall” challenge because of the efficiency of von Neumann architecture. Consequently, there is a growing research interest of exploring emerging nano-devices and new computing architectures to further improve power efficiency [2].

关键词： Artificial neural networks Learning (artificial intelligence) Computer architecture design automation Computational modeling Acceleration

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Automated thermal image segmentation of knee rheumatoid arthritis

Automated thermal image segmentation of knee rheumatoid arth...

引用

International conference on Communications and signal processing

作者： A. B. Suma U. Snekhalatha T. Rajalakshmi Department of Biomedical Engineering SRM University Kancheepuram India

ISBN: (纸本)9781467385497

Rheumatoid arthritis (RA) is one of the systemic autoimmune disorders characterized by chronic inflammation in multiple joints eventually leading to bone erosion and cartilage damage. The main symptoms are (i) morning stiffness (ii) joint swelling (iii) inflammation (iv) neovascularisation (v) cell infiltration and (vi) synovial hyperplasia. Early diagnosis helps in the effective treatment of the disease, however, in the early stages there may not be apparent joint swelling and often present negative radiographs. The common diagnostic methods include Magnetic Resonance (MR) imaging and clinical and health assessment questionnaire. However, MRI is quite expensive; hence, there is a need for cost-effective and safer technique for the diagnosis of RA. Therefore, this study focuses on the application of non-invasive, radiation-free, cost economic technique namely thermography in the diagnosis of early stage RA. The main aim of this paper is to compare various segmentation algorithms, namely manual, colour and k-means image segmentation and to find out the best suitable segmentation algorithm for thermal images. The hot spot region is extracted using three different image segmentation algorithms and compared with the normal thermograph to determine the effective segmentation algorithm in the detection of early stage RA.

关键词： image segmentation image color analysis Manuals Arthritis Algorithm design and analysis Imaging

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