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Robust Single-Shot Fringe Pattern Projection for Three-dimensional Measurements 22

Robust Single-Shot Fringe Pattern Projection for Three-dimen...

引用

2017 22nd International conference on Digital signal processing (DSP)

作者： Budianto Lun, Daniel P. K. Zhu, Weiping Hong Kong Polytech Univ Dept Elect & Informat Engn Ctr Signal Proc EIE Hong Kong Hong Kong Peoples R China Concordia Univ Dept Elect & Comp Engn Montreal PQ Canada

ISBN: (纸本)9781538618950

Although single-shot fringe projection profilometry (FPP) techniques are known to allow effective 3-dimensional measurements (3D) of moving objects, their robustness is often of concern particularly if the object has vivid textures on its surface. Besides, traditional approaches only focus on 3D measurements but ignore the need in many applications of mapping the 3D measurements to the 2-dimensional (2D) textures of the object. In this paper, we present a novel single-shot FPP technique for measuring the 3D model of an object and at the same time estimating its 2D textures. The proposed technique employs a morphological component analysis (MCA) method to separate the fringe patterns and object textures from a fringe image. To further improve the efficiency in identifying the fringe pattern and object texture coefficients, a spatially adaptive thresholding method is developed for MCA. Experimental results show that the proposed technique can significantly improve the robustness of single-shot FPP techniques even when the object has vivid textures on its surface. Besides, it can simultaneously generate the 2D texture image of the object which can hardly be achieved by the traditional single-shot FPP approaches.

关键词： Fringe pattern projection 3-dimensional measurement morphological component analysis wavelets

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Extraction of saliency in images and video: problems, methods and applications. A survey 7

Extraction of saliency in images and video: problems, method...

引用

7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Benois-Pineau, J. Mitrea, M. Univ Bordeaux LaBRI Bordeaux France IMT Telecom SudParis ARTEMIS Dept Evry France

ISBN: (纸本)9781538618424

Rather than meeting the theoretical, methodological and applicative expectancies, the impressing number of state-of-the-art saliency oriented studies raises new fundamental questions about the very nature of this psycho-cognitive process. Such questions encompass fundamental modeling aspects from the very saliency dependency on the representation format to its potential relationship to other fundamental research areas, like information theory, for instance. The present survey, structured according to three main saliency applicative fields (visual quality evaluation, watermarking and task-oriented computer vision) is meant to identify the latest trends of research.

关键词： visual saliency compressed domain saliency applications

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Improved Color Scene Classification System using Deep Belief Networks and Support Vector Machines 5

Improved Color Scene Classification System using Deep Belief...

引用

IEEE International conference on signal and image processing applications (ICSIPA)

作者： Sowmya, V. Ajay, Aleena Govind, D. Soman, K. P. Amrita Univ Amrita Vishwa Vidyapeetham Amrita Sch Engn Ctr Computat Engn & Networking CEN Coimbatore Tamil Nadu India

ISBN: (纸本)9781509055593

In general, the three main modules of the color scene classification systems are image decolorization, feature extraction and classification. The work presented in this paper focuses on image decolorization and classification as two stages. The first stage or objective of this paper is to improve the performance of the color scene classification system using deep belief networks (DBN) and support vector machines (SVM). Therefore, color scene classification system termed as AGMM-DBN-SVM is proposed using the existing feature extraction technique called bags of visual words (BoW) derived from the dense scale-invariant feature transform (SIFT) and adapted gaussian mixture models (AGMM). The second stage of the presented work is to combine the proposed AGMM-DBN-SVM classification models obtained for the two different image decolorization methods called rgb2gray and singular value decomposition (SVD) based color-to-grayscale image mapping techniques to significantly increase the performance of the proposed color scene classification system. The effectiveness of the proposed framework is experimented on Oliva Torralba (OT) scene dataset containing 8 different classes. The classification rate of the proposed color scene classification system applied on OT 8 scene dataset is significantly greater than the one of the existing benchmarks color scene classification system developed using AGMM and SVM.

关键词： Feature extraction Neurons image color analysis Support vector machines Computer architecture Learning systems Adaptation models

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Sparse signal Reconstruction of Compressively Sampled signals Using Smoothed l₀-Norm 5

Sparse Signal Reconstruction of Compressively Sampled Signal...

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IEEE International conference on signal and image processing applications (ICSIPA)

作者： Shah, Jawad Ali Haider, Hassaan Kadir, Kushsairy Abdul Khan, Sheroz Univ Kuala Lumpur British Malaysian Inst Elect Technol Sect Kuala Lumpur Malaysia Int Islamic Univ Fac Engn & Technol Dept Elect Engn Islamabad Pakistan IIUM Malaysia Dept Elect & Comp Engn Kulliyyah Engn Selangor Malaysia

ISBN: (纸本)9781509055593

Compressed Sensing is a novel sampling technique that can be used to faithfully recover sparse signals from fewer measurements than those proposed by the Nyquist theorem. A simple and intuitive measure of sparsity in a signal is l(0)-norm. However, the l(0)-norm function does not satisfy all the axiomatic properties of a true mathematical norm. The discrete and discontinuous nature of l(0)-norm poses many challenges in its applications to recover sparse signals from their subsampled measurements. This paper presents, a novel mathematical function that can be used to closely approximate the l(0)-norm. The proposed function is smooth and differentiable that allows gradient based algorithms to be used in the reconstruction of sparse signals. We use the proposed approximation along with steepest ascent method to develop a complete sparse signal recovery algorithm for the compressed sensing framework. Experimental results have shown that the proposed recovery algorithm outperforms the conventional SL0 method in terms of reconstruction accuracy such as Mean Square Error (MSE) and signal-to-Noise Ratio (SNR).

关键词： Compressed Sensing sparse signal recovery smoothed l(0)-Unorm

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A deep learning approach for detecting and correcting highlights in endoscopic images 7

A deep learning approach for detecting and correcting highli...

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Rodriguez-Sanchez, Antonio Chea, Daly Azzopardi, George Stabinger, Sebastian Univ Innsbruck Dept Comp Sci Intelligent & Interact Syst Innsbruck Austria Univ Groningen Johann Bernoulli Inst Math & Comp Sci Groningen Netherlands

ISBN: (纸本)9781538618424

The image of an object changes dramatically depending on the lightning conditions surrounding that object. Shadows, reflections and highlights can make the object very difficult to be recognized for an automatic system. Additionally, images used in medical applications, such as endoscopic images and videos contain a large amount of such reflective components. This can pose an extra difficulty for experts to analyze such type of videos and images. It can then be useful to detect - and possibly correct - the locations where those highlights happen. In this work we designed a Convolutional Neural Network for that task. We trained such a network using a dataset that contains groundtruth highlights showing that those reflective elements can be learnt and thus located and extracted. We then used that trained network to localize and correct the highlights in endoscopic images from the El Salvador Atlas Gastrointestinal videos obtaining promising results.

关键词： image processing theory image processing tools image processing applications Template Typesetting

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A New Latent generalized Dirichlet Allocation Model for image Classification 7

A New Latent generalized Dirichlet Allocation Model for Imag...

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Ihou, Koffi Eddy Bouguila, Nizar Concordia Univ Fac Engn & Comp Sci Montreal PQ Canada

ISBN: (纸本)9781538618424

As a response to the limitations of the LDA in topic modeling and large scale applications, several extensions using flexible priors have been introduced to expose the problem of topic correlation. Models such as CTM, PAM, GD-LDA, and LGDA have been able to explore and capture semantic relationships between topics. However, many of these models suffer from incomplete generative processes which affect inferences efficiency. In addition, knowing these traditional inference techniques carry major limitations, the new approach in this paper, the CVB-LGDA is an extension to the state-of-the-art. It reconciles a complete generative process to a robust inference technique in a topic correlation framework. Its performance in image classification shows its robustness.

关键词： generalized Dirichlet topic modeling LDA's extensions topic correlation image classification

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Single parameter post-processing method for image deblurring 7

Single parameter post-processing method for image deblurring

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7th International conference on image processing Theory, Tools and applications (IPTA)

作者： Krylov, Andrey Nasonov, Andrey Pchelintsev, Yakov Lomonosov Moscow State Univ Fac Computat Math & Cybernet Moscow Russia

ISBN: (纸本)9781538618424

Numerous algorithms exist for the problem of de convolution of blurred images. But due to ill-posed nature of deconvolution, many images still remain blurry after deblurring. An edge sharpening algorithm is proposed in the paper to further improve the quality of blurry images in edge areas. The method is based on pixel grid warping, its main idea is to move pixels in the direction of the nearest image edges. Warping allows to make edges sharper while keeping textured areas almost intact. Experimental analysis for different optical blur models is performed to optimize the parameters of the proposed method and to show its effectiveness.

关键词： Edge sharpening image deblurring Grid warping Optical blur

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signal processing and Classification for Identification of Clinically Important Parameters During Neonatal Resuscitation 5

Signal Processing and Classification for Identification of C...

引用

IEEE International conference on signal and image processing applications (ICSIPA)

作者： Urdal, Jarle Engan, Kjersti Eftestol, Trygve Kidanto, Hussein Yarrot, Ladislaus Blacy Eilevstjonn, Joar Ersdal, Hege Univ Stavanger Dept Elect Eng & Comp Sci Stavanger Norway Muhimbili Univ Hlth & Allied Sci Dar Es Salaam Tanzania Haydom Lutheran Hosp Res Inst Haydom Manyara Tanzania Laerdal Med AS Strateg Res Stavanger Norway Stavanger Univ Hosp Dept Anesthesiol & Intens Care Stavanger Norway Univ Stavanger Dept Hlth Sci Stavanger Norway

ISBN: (纸本)9781509055593

Neonatal mortality is a global challenge. One million newborns die each year within their first 24 hours as a result of complications during labour and birth asphyxia. Most of these deaths happen in low resource settings. However, basic resuscitation at birth can increase newborn survival. Identification of initial factors and simple therapeutic strategies determinant for neonatal outcome can aid health care workers provide the best follow-up during resuscitation. In this work, the initial condition of the newborn, the treatment given, and early heart rate response from manual bag mask ventilation are parameterized. The features are investigated in a machine learning framework to identify which features are determinant for the different outcomes. Using a selection of the defined features, an identification rate of 89% for newborns in the normal group, and an identification rate of 74% for episodes ending in death was found. This points to the direction of identifying the important factors of newborn survival.

关键词： Pediatrics Ventilation Heart rate Feature extraction Electrocardiography Hospitals

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Application of image retrieval for aesthetic evaluation and improvement suggestion of isolated Bangla handwritten characters 5

Application of image retrieval for aesthetic evaluation and ...

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IEEE International conference on signal and image processing applications (ICSIPA)

作者： Biswas, Mithun Islam, Rafiqul Shom, Gautam Kumar Mohammed, Nabeel Momen, Sifat Mansoor, Nafees Abedin, Anowarul Univ Liberal Arts Bangladesh Dept Comp Sci & Engn Satmasjid Rd Dhaka Bangladesh North South Univ Dept Elect & Comp Engn Dhaka Bangladesh

ISBN: (纸本)9781509055593

Bangla is one of the most widely used languages worldwide. This paper presents an application of image retrieval techniques to automatically judge the aesthetic quality of handwritten Bangla isolated characters. Retrieval techniques are also adapted to give improvement suggestions, with a plan to incorporate the methods in applications which can assist in learning/teaching handwriting. The proposed method borrows key concepts from content-based image retrieval. Our method was tested on the BanglaLekha-Isolated data set, which contains images of 84 Bangla characters, with nearly 2000 samples per character. The data set contains evaluation of the aesthetic quality of the handwriting judged on a scale of 1 - 5. For this work, the dataset was partitioned into a test set of 400 images and a database-set of approximate to 1600 images, per Bangla character. Assuming that a scoring difference of 1 is acceptable, the proposed method achieves an accuracy of 77.39% when using features extracted by a convolutional neural network based autoencoder. Experiments were also done with the popular HOG feature. However, the autoencoder-based results showed clear superiority compared the HOG-based results. Our proposed method for improvement suggestions also shows that it is possible to shows samples from the dataset which will help users improve their handwriting while requiring small changes to their own handwriting.

关键词： Bangla handwriting Aesthetic Evaluation image Retrieval Autoencoder HOG

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Distance Independent Weight Estimation of Eggs from images Using Artificial Neural Networks 25

Distance Independent Weight Estimation of Eggs from Images U...

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25th signal processing and Communications applications conference (SIU)

作者： Sal Varci, Unsal Burak Ayten, Umut Engin Yildiz Tekn Univ Elekt & Haberlesme Muhendisligi Bolumu Istanbul Turkey

ISBN: (纸本)9781509064946

Accurately and fast detection of weight of objects has an important place for lots of academic and industrial application at the present time. In this work, it was aimed to estimate weight of eggs in a distance independent manner using image processing and artificial neural networks (ANN). The constituted system consists of a camera, artificial lighting system, reflector and reference image. Object weight was estimated by processing the acquired image. Feed forward multilayer perceptron (MLP) was preferred as artificial neural network. 250 samples which consist of 4 different brands and 4 different classes (x-large, large, medium, and small) were used for testing and training the system. It was tried to be obtained optimum system by using different feature vectors, different images and different artificial neural network parameters. As accurate classification rate was %47 according to defined by Turkish food codex egg communique and classification values write on the egg cartoon, this rate was increased to %90.5 as a result of this work. All processes were realized by using MATLAB program and toolboxes.

关键词： artificial neural network image processing weight estimation multilayer perceptron egg distance independent system

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