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Development of Low-Cost Vision-Based Falling Sphere Viscometer 5

Development of Low-Cost Vision-Based Falling Sphere Viscomet...

引用

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

作者： Jo, Riady Siswoyo Jo, Hudyjaya Siswoyo Chai, Almon Swinburme Univ Technol Fac Engn Comp & Sci Sarawak Campus Kuching Malaysia

ISBN: (纸本)9781509055593

Falling sphere viscometer is one of the most commonly used techniques in experimentally determining fluid viscosity. This method requires the measurement of the terminal velocity of a falling sphere inside the fluid, which remains a challenging and costly task, especially if high precision is required. This paper presents the development of a low-cost vision-based falling sphere viscometer. The velocity measurement is performed by incorporating two linear image sensors which allow faster frame rate. A specific object detection algorithm based on background subtraction is developed to analyze the image data in real-time. The experimental setup and implementation are also presented.

关键词： Viscosity Microcontrollers Velocity measurement image sensors Electron tubes Object detection Vegetable oils

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Enhanced Correlation Coefficient as a Refinement of image Registration 5

Enhanced Correlation Coefficient as a Refinement of Image Re...

引用

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

作者： Hwooi, Stephen Khor Wen Sabri, Aznul Qalid Md Univ Malaya Fac Comp Sci & Informat Technol Kuala Lumpur 50603 Malaysia

ISBN: (纸本)9781509055593

A study of the effectiveness of Enhanced Correlation Coefficient (ECC) on the performance of feature-based image registration approaches is carried out. This investigation determines if ECC improves image registration performance on datasets which test on invariance to scale, rotation and viewpoint change. Five state-of-the-arts methods are considered, namely KAZE, Binary Robust Invariant Scalable Keypoints (BRISK), Oriented FAST and Rotated Brief (ORB), Speeded-Up Robust Features (SURF), and Scale-Invariant Feature Transform (SIFT). Root-mean-squared error of control points is used to evaluate the image registration performance on datasets taken from the Oxford Robotics Database. A global ranking factor is used to rank each method within a dataset. The efficiency of each method is recorded as a guide for selecting a method for a specific application. Results indicate that ECC improves image registration performance in most cases with a small time addition.

关键词： image registration

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Learning Visual Object and Word Association 5

Learning Visual Object and Word Association

引用

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

作者： Chen, Yie-Tarng Wang, Ting-Zhi Fang, Wen-Hsien Purwanto, Didik Natl Taiwan Univ Sci & Technol Dept Elect & Comp Engn Taipei Taiwan

ISBN: (纸本)9781509055593

This paper presents a new discriminative learning framework to associate the relationship between the objects and the words in an image and perform template matching scheme for complex association patterns. The problem is first formulated as a bipartite graph matching problem. Thereafter, structural support vector machine (SVM) is employed to obtain the optimal compatibility function to encode the association rules between the objects and the words. Moreover, an iterative inference procedure is developed to alternatively infer the association of visual objects and texts and the selection of the template model. Simulations show that the new method outperforms the existing competing counterparts.

关键词： Bipartite graph matching structural SVM image annotation

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Noise Reduction and Enhancement of Contour for Median Nerve Detection in Ultrasonic image 5

Noise Reduction and Enhancement of Contour for Median Nerve ...

引用

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

作者： Katayama, Koutaro Shibata, Keiji Horita, Yuukou Univ Toyama Grad Sch Sci & Engn Educ Toyama 9308555 Japan Univ Toyama Grad Sch Sci & Engn Res Toyama 9308555 Japan

ISBN: (纸本)9781509055593

Three-dimensional nerve information is required for the diagnosis of peripheral neuropathy. We have developed a prototype manipulating device and developed an algorithm for extracting peripheral nerves from the ultrasonic wave images captured using this probe and produce three-dimensional median nerve. Unlike the images captured by artificially manipulating the probe, the images captured by our device captures images of same area only at once. They are partially clear making it easy to extract nerve contours, or partially unclear (blurry) which are difficult to extract. In order to solve this problem, this paper reports that noise reduction and inter-organization edge emphasis are applied to ultrasonic wave images and nerves are extracted using the images.

关键词： Ultrasonic image Median nerve detection Noise reduction Edge enhancement

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A Modified direct data domain STAP Approach Based on Cost Function Reconstruction 5

A Modified direct data domain STAP Approach Based on Cost Fu...

引用

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

作者： He, Jie Feng, Da-zheng Yang, xiao-jun Changan Univ Sch Informat Engn Xian Shaanxi Peoples R China Xidian Univ Key Lab Radar Signal Proc Xian Shaanxi Peoples R China

ISBN: (纸本)9781509055593

In this paper, a hybrid space time adaptive processing (STAP) algorithm of direct data domain (DDD) approach and cost function reconstruction is presented to provide a solution to sample support problem at a low cost of space-time aperture loss. The correlation matrix estimated in DDD approach is partitioned into sub-matrices and two equivalent cost functions are reconstructed. By iteratively solving cost functions, sample support requirements and computational burden can be mitigated. The experiments results on the real data show that the proposed algorithm outperforms conventional DDD method and DDD-JDL with low aperture loss.

关键词： Space time adaptive processing direct data domain approach clutter suppression aperture loss

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image Invariant Description based on Local Fourier-Mellin Transform 5

Image Invariant Description based on Local Fourier-Mellin Tr...

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

作者： Lehiani, Yassine Maidi, Madjid Preda, Marius Ghorbel, Faouzi Ecole Natl Sci Informat ENSI Campus Univ Manouba Manouba 2010 Tunisia ESME Sudria Lab Intelligence Numer & Data 38 Rue Moliere F-94200 Ivry France Telecom SudParis Inst Mines Telecom Dept Artemis 9 Rue Charles Fourier F-91011 Evry France

ISBN: (纸本)9781509055593

In this paper, we present a novel approach for real-time object identification on a mobile platform. First, our system detects keypoints within a scaled pyramid-based FAST detector and then descriptors of the object of interest are computed using an Analytical Fourier-Mellin transform. The Fourier-Mellin is used in similarity studies due to its invariance property and discrimination power. In this approach, we exploited information from the phase of Fourier Transform instead of magnitude applied on patches. The phase carries more information and handle, particularly, rotation and light changes. Finally, experiments are conducted to evaluate the system performances in terms of accuracy, robustness and computational efficiency as well.

关键词： Detectors Robustness Feature extraction Training Fourier transforms image recognition

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Wavelet Based Approaches in Optimization Theory and Practice 6

Wavelet Based Approaches in Optimization Theory and Practice

引用

6th International conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)

作者： Agarwal, Ruchi Salimath, C. S. Alam, Khursheed Sharda Univ Sch Basic Sci & Res Dept Math Greater Noida India

ISBN: (纸本)9781509030125

Panoramic survey of wavelets in optimization techniques is presented as part of ongoing research in applications of wavelet theory to science and technology. The main aim of this article is to study the most efficient techniques and to investigate the extent of improvement achievable by enhancing them with wavelet transform. The article proposes to compile and analyze the comparative performances of various advanced optimization methods using wavelets and the associated transform, highlighting their relative advantages over traditional methods. Numerous applications of optimized wavelets are investigated in biomedical science, neuroscience, and computer science.

关键词： Optimized wavelet Discrete Wavelet Transform Rolling Element Bearings Watermarking image and signal compression

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A Self-Learning Approach for Pan-sharpening of Multispectral images 5

A Self-Learning Approach for Pan-sharpening of Multispectral...

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

作者： Khateri, Mohammad Ghassemian, Hassan Tarbiat Modares Univ Fac Elect & Comp Engn Image Proc & Informat Anal Lab Tehran Iran

ISBN: (纸本)9781509055593

Due to the importance of high-resolution multi-spectral (HRM) images in many remote sensing applications, pan-sharpening techniques have been proposed to increase the spatial resolution of a low-resolution multi-spectral (LRM) image using a high-resolution panchromatic (HRP) image. In this paper, we propose a self-learning approach to pan-sharpen the LRM images. Many structures in a natural image redundantly tend to repeat in the same scale as well as different scales. These similar structures in different levels can be used to reconstruct the HRM bands with more details;in this perspective, we can construct the HRM data from the available HRP and LRM data by using self-similarity in a multi-scale procedure. The proposed method has been applied on GeoEye-1 data and DEIMOS-2 data, and then fused images compared with some popular and state-of-the-art methods in terms of several assessment indexes. The experimental results demonstrate that the proposed method can retain spectral and spatial information of the source images efficiently.

关键词： Pan-sharpening image fusion superresolution multi-scale self-learning panchromatic data multi-spectral data

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Fully automated esophagus segmentation with a hierarchical deep learning approach 5

Fully automated esophagus segmentation with a hierarchical d...

引用

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

作者： Trullo, Roger Petitjean, Caroline Nie, Dong Shen, Dinggang Ruan, Su Normandie Univ UNIROUEN UNIHAVRE INSA RouenLITIS F-76000 Rouen France Univ N Carolina Dept Radiol Chapel Hill NC 27599 USA Univ N Carolina BRIC Chapel Hill NC 27599 USA

ISBN: (纸本)9781509055593

Segmentation of organs at risk in CT volumes is a prerequisite for radiotherapy treatment planning. In this paper we focus on esophagus segmentation, a challenging problem since the walls of the esophagus have a very low contrast in CT images. Making use of Fully Convolutional Networks (FCN), we present several extensions that improve the performance, including a new architecture that allows to use low level features with high level information, effectively combining local and global information for improving the localization accuracy. Experiments demonstrate competitive performance on a dataset of 30 CT scans.

关键词： Esophagus image segmentation Computed tomography Computer architecture Shape Machine learning

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Significance of Contrast and Structure Features for an Improved Color image Classification System 5

Significance of Contrast and Structure Features for an Impro...

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

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

ISBN: (纸本)9781509055593

In general, the three main modules of color image classification systems are: color-to-grayscale image conversion, feature extraction and classification. The color-to-grayscale image conversion is the important pre-processing step which must incorporate the significant and discriminative contrast and structure information in the converted grayscale images as in the original color image. All the existing techniques for color-to-grayscale image conversion preserves the significant contrast and structure information in the converted grayscale images in different manners. Hence, the present work is to analyze the significant and discriminative contrast and structure information preserved in the converted grayscale images using two different decolorization techniques called rgb2gray and singular value decomposition based color-to-grayscale image conversion (SVD) applied in the color image classification systems using the three different proposed features. The three different features for color image classification systems are proposed based on the combination of the existing dense SIFT features and the contrast & structure content computed using color-to-gray structure similarity index (C2G-SSIM) metric.

关键词： Color Gray-scale Feature extraction image color analysis conferences Wheels

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