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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems IV"

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Euclidean proximity function in image processing

Euclidean proximity function in image processing

引用

2016 Signal processing: algorithms, Architectures, Arrangements, and Applications, SPA 2016

作者： Stasik, Pawel M. Department of Control and Systems Engineering Faculty of Computing Science Poznán University of Technology Poznań Poland

ISBN: (纸本)9788362065271

In image processing measuring and valuing a distance between two points is important. The obtained values can be used for determining whether two points are close to each other or to define weights for a filter concentrated around a central element. While there are measures of proximity, neither of them was defined with a such use in mind, mostly concentrating on problem of an optimization. The idea is to turn the Euclidean distance between two points into a measure of how close (or far) two points are from each other, basing on two given ranges. The function was mostly obtained by a theoretical analysis supported with a mathematical calculation and examples of use. As it was proven in the work, the obtained function can be implemented not only to measure proximity, but also as a flexible kernel for image filters, allowing for blurring or edge-detection.

关键词： Edge detection

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PreSight: Enabling Real-Time Detection of Accessibility Problems on Sidewalks

PreSight: Enabling Real-Time Detection of Accessibility Prob...

引用

IEEE Communications Society conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： Zheng Li Mahbubur Rahman Ryan Robucci Nilanjan Banerjee Department of Computer Science and Electrical Engineering University of Maryland Baltimore County

ISBN: (纸本)9781509066001

Accessibility problems such as obstacles on sidewalks can make navigation dangerous for the visually impaired. Detecting these accessibility problems using embedded cameras is a plausible remedy. However, current computer vision algorithms for object detection rely on exhaustive search with high-dimensional features that present a heavy computational burden and incur a long latency, making them non-ideal for real-time object detection on embedded platforms. To address this problem, inspired by prior-based searching schemes from human vision, we accelerate the machine vision process by using scene-specific features to select candidate regions in the view for further processing. Our system, {\hav} achieves speedup by trading off the workload from on-line detection to off-line prior data collection and extraction. We demonstrate a complete, scalable PreSight prototype to accelerate general computer vision object detection algorithms with focus on detecting of sidewalk accessibility problems. Our prototype system automates the process of creating a geo- tagged database of object-specific priors using crowdsourcing and utilizes this prior knowledge to speedup object detection on embedded platforms. Evaluating under two benchmark object detection algorithms, we demonstrate that the detection latency can be reduced by around 8 times with the aid of PreSight.

关键词： image color analysis Object detection Real-time systems Acceleration Computer vision Feature extraction Databases

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Infrared and Visible image Fusion Based on Tetrolet Transform 1

引用

4th International conference on Communications, Signal processing, and systems (CSPS)

作者： Zhou, Xin Wang, Wei Tianjin Normal Univ Coll Elect & Commun Engn Tianjin Peoples R China

ISBN: (数字)9783662498316

ISBN: (纸本)9783662498316;9783662498293

Tetrolet transform has a better directionality of the structure and can express texture features of image precisely in dealing with high-dimensional signal. This paper introduces tetrolet transform into infrared and visible images for fusion to obtain a greater amount of information. First, the tetrolet transform was performed on the images which are fused to obtain high-pass and low-pass subbands on different scales. Then, a method based on local region gradient information was applied to low-pass subbands to get the low-pass fusion coefficients. Finally, the inverse tetrolet transform was utilized to obtain fused image. Using a variety of images to perform fusion experiment, all the results have shown that the fused image has more abundant features and more amount of information by using tetrolet transform. Compared with the traditional fusion algorithms, the fusion algorithm presented in this paper provides better subjective visual effect, and the standard deviation and entropy value would be somewhat increased.

关键词： Infrared image Visible image image fusion Tetrolet transform Multiscale directional analysis

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Holonic Multi Agent System for Data Fusion in Vehicle Classification 10th

Holonic Multi Agent System for Data Fusion in Vehicle Classi...

引用

10th KES conference on Agent and Multi-Agent systems - Technologies and Applications (KES-AMSTA)

作者： Seric, Ljiljana Krstinic, Damir Braovic, Maja Milatic, ivan Mircevski, Aljosa Stipanicev, Darko Univ Split Fac Elect Engn Mech Engn & Naval Architecture Rudera Boskovica 32 Split 210000 Croatia

ISBN: (纸本)9783319398839;9783319398822

In this paper we describe holonic organization of a multi agent system for automatic vehicle classification in a road toll system. Classification of vehicles in road toll systems is based on physical vehicle features and in this paper we focus on axle counting as the first discriminant feature for class determination. Our system relies on two main sensors-video camera and depth sensor. Video image and depth image processing is performed in several holons. The results from individual holons are fused into the final decision on a number of axles of a passing vehicle. We show that fusion of results from individual holons givesmore precise results than individual holons. Holonic organization of the system aids scalability and simplifies inclusion of new sensors and new algorithms.

关键词： Holonic MAS Vehicle classification image processing Data fusion

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Automatically diagnosing HER2 amplification status for breast cancer patients using large FISH images

Automatically diagnosing HER2 amplification status for breas...

引用

IEEE Signal processing and Communications Applications (SIU)

作者： Salar Razavi Gökhan Hatipoğlu Hülya Yalçın Electronics and Telecommunication Engineering Department Istanbul Technical University Virasoft Yazılım Istanbul Turkey

ISBN: (纸本)9781509064953

Fluorescence in situ hybridization (FISH) is a technique that prepares acceptable results for molecular imaging biomarkers to precisely and dependably detect and diagnose disorders which are sign of cancers. Since contemporary manual FISH signal analysis is low-effective and inconsistent, it is an attractive research area to develop automated FISH image scanning systems and computer-aided diagnosis (CAD) schemes. The gene expression of epidermal growth factor receptors 2 (HER2) is highly related to results of patients with probable breast cancer. Although FISH technology outperforms other methods, yet it has so many drawbacks. Traditional approaches on FISH analysis are performed manually by clinician. This lets the results are highly dependent to human eye. Also FISH test colors constitutes of dark blue and black regions, it is reasonable that human eye will fail to distinguish between colors. Therefore, the success of computer vision algorithms compared to human eye in analyzing gene expression rate in FISH images will be discussed in this study. Another objective of this study is to expand a CAD program to evaluate HER2 status using acquired images that have MIRAX format. Different large FISH images were chosen for this study from pathology laboratory from Acibadem Maslak hospital. The proposed CAD scheme first applies pre-processing median and gaussian filters. An adaptive thresholding method followed by a watershed segmentation algorithm is employed to segment cells of interest areas. Furthermore, analyzable cells are found and non-detectable cells because of cell overlapping or image staining are discarded. The scheme then splits the detected analyzable region of interest into two red and green color spaces which is also followed by application of a scanning algorithm to detect the CEP17 green and HER2/neu red FISH signals separately. Finally, the proposed method calculates the ratio between independent green and red FISH signals of all analyzable cells identi

关键词： Fish Breast cancer image color analysis image segmentation Manuals Pathology

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Combined Imaging System for Taking Facial Portraits in Visible and Thermal Spectra

引用

8th International conference on image processing and Communications (IP and C)

作者： Jasinski, Piotr Forczmanski, Pawel West Pomeranian Univ Technol Fac Comp Sci & Informat Technol Zolnierska Str 52 PL-71210 Szczecin Poland

ISBN: (纸本)9783319238142;9783319238135

This work explores the subject of thermal imagery in the context of face recognition. Its aim is to create a database of facial images taken in both thermal and visual domains. To achieve this, a specialized photographic stand was designed, which allows simultaneous capture of images from IR thermal camera and SLR digital camera. To ensure precision, stability and fluency of photographic sessions, a Matlab application has been developed, through which it is possible to remotely control both devices, as well as automatically download captured images onto a hard drive and save them within an organized folder structure. Additionally, several image fusion techniques have been implemented in order to effectively combine visual and thermal data for use in face recognition algorithms.

关键词： Thermovision Biometrics Face Database image fusion

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Robotic Imitation of Human Hand Using RGB Color Gradient Mapping

Robotic Imitation of Human Hand Using RGB Color Gradient Map...

引用

International conference on Artificial Intelligence and Evolutionary Computations in Engineering systems (ICAIECES)

作者： Thyagaraj, T. Abhishek, Kumar Brunda, N. S. Ranjan, Rakesh Kini, Nikita VTU AICTE Dept Elect & Commun Engn BMSIT VTU Campus Belagavi Belagavi 590018 Karnataka India

ISBN: (纸本)9788132226567;9788132226543

The state-of-the-art developments in robotics reveal a scenario wherein human motion imitation has been developed through advancements in features and performance of sensors. Most of such robots uses flex sensors to acquire the information about the orientation of the body being imitated. However, these are slow and are highly vulnerable to damages and physical changes. There are image processing algorithms that are focused on a robots learning through ANN and are not into imitation without memory. This paper presents an overview of research attempts to use a robotic assembly to imitate a real object using image processing. The paper describes results in force, tactile and visual sensing, sensor-based control, and the configuration of a test-based robot integrated system for imitation of a human hand, using vision through image processing using RGB scheme;and one-on-one mapping for the acquisition of the current position of a body and orientation of the various parts of the robot in same fashion. This research has resulted in the development of a prototype capable of imitation and its applications are in the areas of medicine, defense, safety, and explorations for both research and commercial applications.

关键词： Robotic vision Color mapping Median filtering Robot-arm Embedded module image processing Robotics Robotic arm Human imitation Motion tracking Motion sensing Robotic vision Sensor-based robots Flex sensors Embedded systems Integrated systems Artificial neural networks Matlab RGB scheme

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Color Space Optimization for Lacunarity Method in Analysis of Papanicolaou Smears

引用

8th International conference on image processing and Communications (IP and C)

作者： Oszutowska-Mazurek, Dorota Mazurek, Przemyslaw Sycz, Kinga Waker-Wojciuk, Grazyna Higher Sch Technol & Econ Szczecin Klonowica 14 St PL-71244 Szczecin Poland West Pomeranian Univ Technol Dept Signal Proc & Multimedia Engn 26 Kwietnia 10 St PL-71126 Szczecin Poland Independent Publ Voivodeship United Hosp Dept Pathomorphol Arkonska 4 St PL-71455 Szczecin Poland

ISBN: (纸本)9783319238142;9783319238135

There are numerous cells nuclei analysis algorithms. The lacunarity is the texture analysis algorithm and could be applied for binary or grayscale images of cells nuclei. The cells in Papanicolaou process are stained so numerous conversions to grayscale or binary images are possible. The optimization of RGB color space using weights is proposed for polynomial based analysis using lacunarity and the cell area of binary image. Obtained results show significant differences for best and worst cases for the number of cells of atypical and correct classes with similar cells area.

关键词： Lacunarity image analysis Cytology

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Removal of Spurious Edges from Thinned Character image: A Survey

Removal of Spurious Edges from Thinned Character Image: A Su...

引用

International conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： Khatri, Nikita Goswami, Mukesh M. Dharamsinh Desai Inst Technol Informat Technol Nadiad India

ISBN: (纸本)9781467399395

Thinning is an important pre-processing step in many shape based character and word recognition systems. The one-pixel wide thinned character image is useful for identifying the shape of various strokes used to from the character, which is helpful in many applications such as word spotting in the document image, content-based document image retrieval, character and word classification, etc. However, all thinning algorithms generate unwanted spurious edges. As a result, the shape of the stroke is distorted which in turn limits the accuracy of stroke recognition in characters. Thus, removal of these spurious edges from thinned image will improve the state of the art in stroke recognition and benefit many applications stated above. This paper presents a survey of various techniques used for removal of spurious edges from thinned character image and tries to identify the challenges and research gaps in the problem.

关键词： Thinning structural noise removal spurious edges thinned character image

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image formation methods in quantitative acoustic microscopy

Image formation methods in quantitative acoustic microscopy

引用

IEEE International conference on Acoustics, Speech and Signal processing

作者： Jonathan Mamou Daniel Rohrbach F. L. Lizzi Center for Biomedical Engineering Riverside Research New York USA

ISBN: (纸本)9781509041183

Quantitative acoustic microscopy (QAM) is an imaging modality which uses very-high-frequency ultrasound (i.e., >200 MHz) to form two-dimensional (2D) quantitative images of acoustical and mechanical properties of soft tissues with microscopic resolution (i.e., better than 8 μm). The key component of a QAM system is the ultrasound transducer which must be broadband, have a very small F-number (i.e., <;1.2), and good sensitivity. In this study, two QAM systems based on a 250-MHz and a 500-MHz transducer are presented, yielding 2D quantitative images at spatial resolution of 7 μm and 4 μm respectively. Thin tissue sections obtained using a microtome or cryotome are raster scanned with precise motors and pulse-echo RF signals are digitized. Inverse models are then used to process each RF signal individually to estimate acoustic impedance, speed of sound, and acoustic attenuation as well as derived parameters such as bulk modulus, mass density, and compressibility. To illustrate the QAM technology and signal processing algorithms, images from cancerous human lymph nodes and ophthalmologic samples are presented and coregistered with histology photomicrographs.

关键词： Ultrasound acoustic microscopy very-high frequency acoustic microscopy Very High Frequency Ultrasonic Waves ultrasonic transducers Quadrature amplitude modulation radio frequency signal Sound attenuation MICROTOME Raster processing Acoustics

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