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检索条件"任意字段=2016 Conference on Design and Architectures for Signal and Image Processing, DASIP 2016"

共 951 条记录，以下是761-770 订阅

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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...

引用

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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ANALYSIS AND APPLICATIONS OF MODIFIED NON-SUBSAMPLED CONTOURLET TRANSFORM

ANALYSIS AND APPLICATIONS OF MODIFIED NON-SUBSAMPLED CONTOUR...

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International conference on Recent Trends in Engineering, Science & Technology

作者： H. Devanna G. A. E. Satish Kumar M. N. Giriprasad ECE Department St.Johns College of Engineering & Technology ECE Department Vardhaman College of Engineering ECE Department JNTU College of Engineering Anatapur

ISBN: (纸本)9781785617850;9781785617867

A number of image processing tasks are efficiently carried out using the domain of invertible linear transformation. Various areas of application such as image compressing, image denoising, image coding etc. are efficiently been carried out using different types transformation techniques. An effective transform capture the essence of a given signal with defined basis functions. The set of basis functions completely characterizes the transform and these sets can be redundant or non-redundant in nature. In the redundant approach, it is possible to improve the set of basis function so as the representation is more efficient in capturing signal behavior. In addition, redundant representations are generally more flexible and easier to design. In various applications such as denoising, image enhancement, contour detection etc. a redundant representation significantly outperforms the non-redundant approach.

关键词： Transform image Contour Basis functions Redundant Redundant basis functions Transform contour image images image processing task given signal imagery (Psychotherapy)

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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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Considerations on performance, cost and power consumption of candidate 100G EPON architectures

Considerations on performance, cost and power consumption of...

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International conference on Transparent Optical Networks

作者： Z. Vujicic A. Shahpari B. Neto N. Pavlovic A. Almeida A. Tavares M. Ribeiro S. Ziaie R. Ferreira R. Bastos A. Teixeira Instituto de Telecomunicacoes University of Aveiro Aveiro Portugal

An overview of several candidate architectures for 100 Gb/s capable optical access networks is presented. Considerations for their system requirements are outlined in regards to performance, cost and energy efficiency... 详细信息

ISBN: (纸本)9781509014682

关键词： Optical signal processing Dispersion Sensitivity Chirp Optical transmitters Transceivers Modulation

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Identification of Tumor area from Brain MR image

Identification of Tumor area from Brain MR Image

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IEEE signal processing and Communications Applications (SIU)

作者： Ömer Kasım Ahmet Emin Kuzucuoğlu Milli Eğitim Bakanlığı İstanbul Türkiye Marmara Universitesi Istanbul Istanbul TR

The analysis of Magnetic Resonance image has an important role in definite detection of Brain Tumor. The shape, location and size of tumor are examined by Radiology specialist to diagnose and plan treatment. In the intense work pace, it's not possible to get results quickly. At this scheme, unnoticed information can be recovered by an image processing algorithm. In this study, at database images which are collected from REMBRANT were cleared from noise, transformed with Karhunen Loeve Transform to gray level and segmented with Pott's Markov Random Field Model. This hybrid algorithm minimizes the data loss, contrast and noise problems. After segmentation stage, shape and statistical analysis are performed to get feature vector about Region of Interest. The images are classified as existing tumor or not existing tumor. The algorithm can recognize the presence of tumor with 100% and tumor's area with 95% accuracy. The results are reported to help the specialists.

关键词： Tumors Markov processes Brain modeling Algorithm design and analysis image segmentation Shape Transforms

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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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Neural Network Based Skeleton Recognition and Sudoku Solving

Neural Network Based Skeleton Recognition and Sudoku Solving

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International conference on signal processing and Integrated Networks (SPIN)

作者： Gaurav Chitranshi Sharad Tiwari RudraPratap Singh Prateek S Sengar Dept. of Electronics and Communication Engineering Amity University Noida India

ISBN: (纸本)9781467391986

This paper presents the development of an Neural Network Based Skeleton Recognition and Sudoku Solving. The main objective of this work is to recognize the number and its corresponding position from a Sudoku image and also to solve any valid Sudoku. The recognition system is designed through an artificial neural network model. The neural network uses the mechanism of feedforwardbackpropogation technique where minimizing error is taken into consideration. Using the gradient of the criteria-field helps in weights modification and thus optimizes the system. The Sudoku is then solved using the backtracking algorithm which is a trial and error method. It takes into account one selection at a time from the multiple choices (1-9). This technique can solve any valid Sudoku. The final result is made to display on the original image by using the database. The database consist of template numbered images which is obtained from the segmentation from the Sudoku images. The system is well trained and effective in recognizing the number compared with the traditional template matching.

关键词： Skeleton signal processing algorithms Neural networks image recognition Databases Pattern recognition Algorithm design and analysis

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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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Automated thermal image segmentation of knee rheumatoid arthritis

Automated thermal image segmentation of knee rheumatoid arth...

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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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Unsupervised approach for change map generation

Unsupervised approach for change map generation

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International conference on Communications and signal processing

作者： Harshada N. Mahulkar Bhakti Sonawane Computer Engineering Department Shah and Anchor kutcchi College of Engineering Mumbai India

ISBN: (纸本)9781467385497

Change detection is the process of automatically identifying and analyzing region that have undergone spatial or spectral changes from multi temporal images. Detecting and representing change provides valuable information of the possible transformations a given scene has suffered over time. Change detection is used in several applications (eg. Disaster management, deforestation, urbanization, etc). In the proposed unsupervised method co-registered and radiometrically corrected temporal images are used as input. Using this, absolute valued image and log ratio image is calculated to get difference image. These difference images are fused using Discrete Wavelet Transform (DWT). Then, min-mean normalization is applied to the get filtered data. The normalized data is clustered into two groups using K-means clustering algorithm as changed pixels and unchanged pixels. Experiment result is also calculated using two different ways. In first, fused image data is given to Principal Component Analysis (PCA) and clustering is done using K-means algorithm and in second way Fuzzy c-means clustering algorithm is used to cluster image data.

关键词： Discrete wavelet transforms Principal component analysis Clustering algorithms Algorithm design and analysis Change detection algorithms Remote sensing

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