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

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Adaptive algorithm of conforming image matching 5

Adaptive algorithm of conforming image matching

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Data Science Session at the 5th International conference on Information Technology and Nanotechnology, DS-ITNT 2019

作者： Fursov, V.A. Goshin, Ye.V. Pugachev, K.G. Samara National Research University Moskovskoe Shosse 34 Samara443086 Russia Image Processing Systems Institute of RAS Branch of the FSRC Crystallography and Photonics RAS Molodogvardejskaya street 151 Samara443001 Russia

This paper presents an adaptive algorithm of conforming image matching based on the principle of conformity. The algorithm consists of several main stages. At the first stage, we find the corresponding points using a minimum value of conformity as the measure of points’ similarity. We define a conformity function as the sum of all possible combinations of squared differences of pixel intensity values on the fragments that are matched. Then, we perform an adaptive procedure of errors correction considering an intensity gradient distribution. An important feature of the algorithm is the finding of error points using a criterion of maximum value of samples’ conformity for every fragment of the disparity map. The results of experiments on the "Teddy" test images are shown. © 2019 CEUR Workshop Proceedings.

关键词： Adaptive algorithms

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Learning Deep Feature Representation for Face Spoofing 2nd

Learning Deep Feature Representation for Face Spoofing

引用

2nd International conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2018

作者： Srinivasa Perumal, R. Santosh, K.C. Chandra Mouli, P.V.S.S.R. School of Information Technology and Engineering Vellore Institute of Technology VelloreTamil Nadu India Department of Computer Science University of South Dakota Vermillion United States Department of Computer Applications National Institute of Technology JamshedpurJharkhand India

ISBN: (纸本)9789811391804

Biometrics is an emerging research area due to its easiness in identification of the person. Face Spoofing is the challenging task in face recognition systems because the human can easily trickster the system by presenting the video or photograph of the person. Many approaches are providing good results in face spoofing, but still it is challenging in intra and cross database validation. Deep learning algorithms have shown significant results in the intra and cross database. This paper used deep learning for extracting the inclusive and favorable features of the person from the face. The extracted features are used for classifying the face image as a real face or genuine face. The performance of the method is evaluated through statistical measures. The experiments were carried out NUAA and CASIA database. The method attained most promising results than other face spoofing methods. © 2019, Springer Nature Singapore Pte Ltd.

关键词： image classification

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Color Correction for Stereoscopic images Based on Gradient Preservation

Color Correction for Stereoscopic Images Based on Gradient P...

引用

Computing conference, 2019

作者： Liu, Pengyu Niu, Yuzhen Chen, Junhao Shi, Yiqing College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fujian China

ISBN: (纸本)9783030228705

Color correction can eliminate the color difference between similar images in image stitching and 3D video reconstruction. The result images generated by the local color correction algorithms usually show structure inconsistency problem with the input images. In order to solve this problem, we propose a structure consistent color correction algorithm for stereoscopic images based on gradient preservation. This method can not only eliminate color difference between reference and target images, but also optimize structure between the input target image and the result image. Firstly, the algorithm extracts the structure information of the target image and style information of the reference image using the SIFT algorithm and generates the structure image and the pixel matching image. Then an initial result image is generated by local pixel mapping. Finally the initial result image is iteratively optimized by the gradient preserving algorithm. The experimental results show that our algorithm can not only optimize the structure inconsistency, but also effectively process image pairs with large color difference. © 2019, Springer Nature Switzerland AG.

关键词： Mapping

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visualizing Salient Network Activations in Convolutional Neural Networks for Medical image Modality Classification 2nd

Visualizing Salient Network Activations in Convolutional Neu...

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2nd International conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2018

作者： Rajaraman, Sivaramakrishnan Antani, Sameer Lister Hill National Center for Biomedical Communications National Library of Medicine BethesdaMD20894 United States

ISBN: (纸本)9789811391835

Convolutional neural network (CNN) has become the architecture of choice for visual recognition tasks. However, these models are perceived as black boxes since there is a lack of understanding of their learned behavior from the underlying task of interest. This lack of transparency is a drawback since poorly understood model behavior could adversely impact subsequent decision-making. Researchers use novel machine learning (ML) tools to classify the medical imaging modalities. However, it is poorly understood how these algorithms discriminate the modalities and if there are implicit opportunities for improving visual information access applications in computational biomedicine. In this study, we visualize the learned weights and salient network activations in a CNN based Deep Learning (DL) model to determine the image characteristics that lend themselves for improved classification with a goal of developing informed clinical question-answering systems. To support our analysis we cross-validate model performance to reduce bias and generalization errors and perform statistical analyses to assess performance differences. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Decision making

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Portable Blood Typing Device Using image Analysis 4

Portable Blood Typing Device Using Image Analysis

引用

4th IEEE International conference on Consumer Electronics - Asia, ICCE-Asia 2019

作者： Cruz, Jennifer C. Dela Garcia, Ramon G. Diaz, Annissa vi C. Diño, Angelika Mae B. Nicdao, Danielle Jane I. Venancio, Christine Shayne S. Mapúa University Philippines

ISBN: (纸本)9781728133362

Blood type can be determined by the presence or absence of antigens in the red blood cells, and can be classified by the ABO (A, B, AB, O) and Rh D (either positive or negative) systems. Knowing one's blood type is one of the most crucial steps before blood transfusion or any medical operations to prevent the risk of receiving incompatible blood that could lead to adverse or even fatal reactions to patients. Although fully automated blood testing instruments are already being used in some major hospitals, its large size and long processing time, limit its ability to be used in emergency situations. Hence, during onsite blood typing, the traditional or the slide method is being used, which is less accurate due to human errors. This paper presents a raspberry pi based image processing system that is capable of determining all eight types of blood using Canny Edge and Contour Detection. All blood types detected by the proposed system matched that of the known blood samples for the controlled testing of all five samples with five trials each sample for the known A+, B+ AB+, O+, A-, B-, AB- and O-. Uncontrolled testing was also performed to compare the results of the ten random blood types identified by the proposed prototype to the results obtained from test tube method. All these ten samples matched the results obtained from the clinical laboratory. This portable and automated device could avoid human errors, without risking accurate results that could be obtain in a short period of time. © 2019 IEEE.

关键词： Antigens

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Specular reflection detection algorithm for endoscopic images 17

Specular reflection detection algorithm for endoscopic image...

引用

17th image processing: algorithms and systems conference, IPAS 2019

作者： Voronin, V. Semenishchev, E. Zelensky, A. Agaian, S. Don State Technical University Dept. of Radio-Electronics Systems Gagarina 1 Rostov on Don Russia Moscow State University of Technology "STANKIN" Moscow Russia CUNY College of Staten Island Dept. of Computer Science New York United States

Endoscopy is a process that allows viewing/ visualize the inside of a human body. In this article, we propose a specular reflection detection algorithm for endoscopic images that utilizes intensity, saturation and gradient information. The proposed algorithm is a two-stage procedure: (a) image enhancement using an adaptive alpha-rooting algorithm and (b) an efficient reflection detection algorithm in the HSV color space. The extensive computer simulations show a significant improvement over state-of-the-art results for specular reflection detection and segmentation accuracy. © 2019, Society for Imaging Science and Technology.

关键词： Endoscopy

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Uncertainty quantification for semi-supervised multi-class classification in image processing and ego-motion analysis of body-worn videos 17

Uncertainty quantification for semi-supervised multi-class c...

引用

17th image processing: algorithms and systems conference, IPAS 2019

作者： Qiao, Yiling Shi, Chang Wang, Chenjian Li, Hao Haberland, Matt Luo, Xiyang Stuart, Andrew M. Bertozzi, Andrea L. University of Chinese Academy of Science Beijing China Renmin University of China Beijing China University of California Los Angeles Los AngelesCA United States California Polytechnic State University San Luis ObispoCA United States California Institute of Technology PasadenaCA United States

Semi-supervised learning uses underlying relationships in data with a scarcity of ground-truth labels. In this paper, we introduce an uncertainty quantification (UQ) method for graph-based semi-supervised multi-class classification problems. We not only predict the class label for each data point, but also provide a confidence score for the prediction. We adopt a Bayesian approach and propose a graphical multi-class probit model together with an effective Gibbs sampling procedure. Furthermore, we propose a confidence measure for each data point that correlates with the classification performance. We use the empirical properties of the proposed confidence measure to guide the design of a human-in-the-loop system. The uncertainty quantification algorithm and the human-in-the-loop system are successfully applied to classification problems in image processing and ego-motion analysis of body-worn videos. © 2019, Society for Imaging Science and Technology.

关键词： Motion analysis

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Preliminary design of a multipurpose UAV situational awareness platform based on novel computer vision and machine learning techniques

Preliminary design of a multipurpose UAV situational awarene...

引用

South Eastern European Design Automation, Computer Engineering, Computer Networks and Social Media conference (SEEDA-CECNSM)

作者： Evangelos Maltezos Lazaros Karagiannidis Thanasis Douklias Aris Dadoukis Angelos Amditis Evangelos Sdongos Institute of Communication and Computer Systems (ICCS) Zografou Greece

ISBN: (数字)9781728164458

ISBN: (纸本)9781728164465

There has been an increased trend in the use of Unmanned Aerial Vehicles (UAVs) providing essential assistance and enhanced situational awareness in various application domains. Considering the sensing and intelligent processing capabilities of UAV platforms, operational managers are able to make smart decisions by having a more complete picture in real-time about the state of the managed event. In this paper, a preliminary design of a multipurpose UAV based situational awareness platform is proposed by exploiting advanced on-board processing capabilities and efficient computer vision, image processing and machine learning techniques. The proposed design consists of aerial and terrestrial surveillance assets able to provide rapid and reliable real-time event information of areas of interests in emergency operations. Experimental results are provided using RGB and thermal video datasets and applying novel object detection and tracking algorithms. The results show the utility and the potentials of the proposed design, while future directions for extension and optimization of the multipurpose UAV based situational awareness system are presented.

关键词： UAV situational awareness computer vision machine learning object detection object tracking situational awareness images computer vision Unmanned Aerial Vehicle Object detection Awareness drone honey bees preliminary design tracking objects Artificial Intelligence Machine Learning

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Practical Issues in Contingency Planning for UAVs with Engine Failures 2019

Practical Issues in Contingency Planning for UAVs with Engin...

引用

Proceedings of the 3rd International conference on vision, image and Signal processing

作者： Bulent Ayhan Chiman Kwan Signal Processing Inc. Medical Center Dr. Rockville MD USA

ISBN: (纸本)9781450376259

Unmanned Air Vehicles (UAV), also known as Unmanned Air systems (UAS), are gaining more attention in recent years. Some potential commercial applications with UAVs may include small cargo transport, search and rescue operations, drought and pest monitoring, etc. It is well-known that UAVs are less reliable as compared to manned aircraft. This is probably one of the consequential reasons that Federal Aviation Administration (FAA) is hesitant to open up the national airspace (NAS) and imposes tight restrictions to UAVs. Reliability of UAVs can be improved using engines and equipment with high quality and fault diagnostic algorithms using machine learning and artificial intelligence techniques, and robust and fault tolerant controllers. Despite the above measures, engine and equipment malfunctions may still appear in various applications. In this paper, we summarize some recent research results by us with respect to engine failures encountered in UAVs. Due to engine failure, there is limited hanging time and the mishap UAV needs to land preferably in an unpopulated area. In particular, we explicitly address some practical issues related to engine failures.

关键词： Contingency Planning Engine Failures Uavs

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A Question Answering System of Ethnic Minorities Based on Knowledge Graph

A Question Answering System of Ethnic Minorities Based on Kn...

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Symposium of image, Signal processing, and Artificial vision (STSIVA)

作者： Jiayi Li Shuang Liu Hui Yang Simon Kolmanič Dalian Minzu University Liaoning China University of Maribor Koroska Slovenia

ISBN: (数字)9781728170862

ISBN: (纸本)9781728170879

In recent years, Question Answering System has become a main focus of human machine interaction. Using the question answering system for information retrieval is convenient and efficient. Traditional question answering systems mostly use template matching. The question and answer data sets usually rely on manual design. The question and answer system implemented by this method has a quick query response and can answer relatively complex questions. But manually defining templates and rules is time-consuming and laborious. Therefore, this paper introduces the knowledge graph in the process of constructing the question answering system. The proposed method combines knowledge graph with question answering systems to realize an intelligent question answering system in the field of ethnic minorities, so as to spread ethnic minority knowledge and promote ethnic minority culture. The construction of a question answering system is mainly divided into two modules: question analysis and answer generation. The question analysis module includes named entity recognition, similarity calculation and question classification. The answer generation module includes entity mapping and graph retrieval. The experimental results show that our approach by combined with natural language processing technology and domain knowledge graph can well accurately feedback the answers to user queries. And the answer accuracy of the question answering system can reach about 81%.

关键词： Semantics Manuals Knowledge discovery Information retrieval Natural language processing Classification algorithms Informatics

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