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Segmentation of Clusters Nuclei Based on Intensity and Texture in Phase Contrast Image using H-Maxima Transformation

Segmentation of Clusters Nuclei Based on Intensity and Textu...

引用

IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)

作者： Vinothini, A. Prasad, B. KS Rangasamy Coll Technol Dept Elect & Commun Engn Namakkal India

ISBN: (纸本)9781467393379

The nucleus segmentation is the most important and tedious process in medical image analysis. The proposed method has three stages: preprocessing, h-maxima transformation based watershed segmentation and texture analysis. First, the preprocessing stage uses top-hat fIlter to increase the contrast of nuclei and reduce the non-uniform illumination, imaging artifacts in the input image. In second stage, the segmentation of nuclei consists of a distance transformation, h-maxima transformation and watershed segmentation. The markers are used to obtain segments of the nuclei in the h-TMC watershed segmentation. To detect the single marker in nucleus, we usethese transformations. Due to imaging artifacts, prolonged cell cytoplasm in the contrast image, nuclei may falsely be segmented and it leads to an inaccurate analysis of the cell image. To identify and remove the non-nuclei segments. The third stage of texture analysis is followed. The texture with adaboost algorithm is used for non-nucleus identification.

关键词： adaboost algorithm h-TMC watershed segmentation Nuclei segmentation Phase contrast image

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Research on Recognition Method of Learning Concentration Based on Face Feature 8

Research on Recognition Method of Learning Concentration Bas...

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IEEE International Conference on Cybernetics and Intelligent Systems (CIS) / IEEE Conference on Robotics, Automation and Mechatronics (RAM)

作者： Kong, Yaguang Li, Wenqian Hangzhou Dianzi Univ Inst Informat & Control Hangzhou Zhejiang Peoples R China Hangzhou Dianzi Univ Sch Automat Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781538631355

With the rapid development of information and Internet technology, online education has become an increasingly popular way of education. Online education allows learners to learn any content at any place and at any time. However, in the process of online learning, the learners' learning mood state is usually not paid attention to. Due to a long time to face monotonous non-communication computer screen, Internet learners are prone to physical or psychological fatigue, resulting in decreased learning efficiency. In view of this phenomenon, taking into account the characteristics of online learning, we define three learning-related expressions: focus, fatigue and normal. we make use of haar-based adaboost algorithm based on the face detection method to detect the network learners face area, According to the established facial expression model, the facial features of the network learners are extracted, including the eye and mouth features, and then the fuzzy control theory is used to fuzzify the obtained feature data. Finally, the method of comprehensive decision is used to judge the network learning the state of study. The experimental results show that the method used in this paper can be used to classify learners' learning status correctly.

关键词： face detection adaboost algorithm learning fatigue fuzzy control

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Face Recognition algorithm Using Wavelet Decomposition and Support Vector Machines

Face Recognition Algorithm Using Wavelet Decomposition and S...

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International Symposium on Optomechatronic Technologies (ISOT)

作者： Wang, Wei Sun, Xiang-yu Karungaru, Stephen Terada, Kenji Univ Tokushima Tokushima 770 Japan HUNAN RUNBANG 810 TECHNOL LTD Changsha Peoples R China

ISBN: (纸本)9781467328777

Face recognition algorithm is a very promising technique in biometric authentication. However, the recognition precision can be affected by many factors, such as feature extraction method and classifier selection. In this paper, a novel algorithm for face recognition is presented according to the advances of the wavelet decomposition technique and the Support Vector Machines (SVM) model. The extracted features from human images by wavelet decomposition are less sensitive to facial expression variation. As a classifier, SVM provides high generation performance without transcendental knowledge. First, we detect the face region using an improved adaboost algorithm. Second, we extract the appropriate features of the face by wavelet decomposition, and compose the face feature vectors as input to SVM. Third, we train the SVM model by the face feature vectors, and then use the trained SVM model to classify the human face. In the training process, three different kernel functions are adopted: Radial basis function, Polynomial and Linear kernel function. Finally, we present a face recognition system that can achieve high recognition precision and fast recognition speed in practice. Experimental results indicate that the proposed method can achieve recognition precision of 96.78 percent based on 96 persons in Ren-FEdb database that is higher than other approaches.

关键词： face detection adaboost algorithm wavelet decomposition Support Vector Machines SURF method

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Elderly Care Notification System using Hand Posture Recognition

Elderly Care Notification System using Hand Posture Recognit...

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4th International Conference on Digital Information and Communication Technology and it's Applications (DICTAP)

作者： Sawasdee, Sutang Pumrin, Suree Chulalongkorn Univ Fac Engn Dept Elect Engn Bangkok 10330 Thailand

ISBN: (纸本)9781479937240

This paper proposes a hand posture recognition as an assistive tool for elderly care. The system uses Haar-like feature, Principle Component Analysis (PCA), and simulation web server for detection, recognition, and alert by order. Our system interprets the hand sign captured by web camera and alerts a caregiver via smart phone. Besides, a caregiver can also periodically check needs of an elder from a smart phone. So a caregiver can do other tasks more efficiently because he/she need not to be with an elder at all times. The empirical results show satisfactory performance of PCA and contour detection with hand posture recognition.

关键词： Hand posture recogniotion elderly care Haar-like feature adaboost algorithm Principle Component Analysis

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Automatic Fault Recognition for Losing of Train Bogie Center Plate Bolt

Automatic Fault Recognition for Losing of Train Bogie Center...

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14th IEEE International Conference on Communication Technology (ICCT)

作者： Li, Nan Wei, Zhenzhong Cao, Zhipeng Wei, Xinguo BUAA Beijing Peoples R China

ISBN: (纸本)9781467321013;9781467321006

This paper proposes an automatic recognition method for losing of train bogie center plate bolt (TBCPB), which initially locates the bolt region based on gray projection and spatial filter, and then acquires the accurate position of bolt region combined with its gradient feature, finally extracts the Haar-like features of bolt region and designs a classifier based on the adaboost algorithm. Results of experiments demonstrate that the method compresses noise effectively and overcomes the complexity of various backgrounds. It is also a robust method to images with poor quality, such as blur, poor illumination and excess exposure. The average fault recognition accuracy is 95.9%.

关键词： automatic recognition Haar-like feature adaboost algorithm cross-validation

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A New algorithm for Fatigue Detection in Driving

A New Algorithm for Fatigue Detection in Driving

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8th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)

作者： Chen, Dongwei Wang, Zhen Zhuo, Qiusheng Wu, Fang Beijing Inst Technol Zhuhai Guangdong Peoples R China

ISBN: (纸本)9783642549243;9783642549236

Eye state tracking for driving is the key problem in fatigue detection, and it has been proved to be effective and popular method in fatigue driving. In this paper, we present a new algorithm framework for fatigue driving. We first recognize human eyes with adaboost algorithm, then an improved Otsu algorithm is modified to automatically adapt to varied environments. Furthermore, we propose an effective algorithm based on dynamic sliding window in order to compute proper threshold between open and close eye window. Finally, we estimate the different level of fatigue driving with improved percentage of eyelid closure time (PERCLOS) algorithm. Human eye images are captured with camera in real time, and our method is simulated on personal computer. The comparative experiments demonstrate that the proposed algorithm framework can effectively discriminate the level of fatigue state in driving.

关键词： adaboost algorithm Adaptive Otsu algorithm Feature extraction Dynamic sliding window detection Fatigue driving

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An Improved Multi-label Classification Ensemble Learning algorithm 6

An Improved Multi-label Classification Ensemble Learning Alg...

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6th Chinese Conference on Pattern Recognition (CCPR)

作者： Fu, Zhongliang Wang, Lili Zhang, Danpu Chinese Acad Sci Chengdu Inst Comp Applicat Chengdu Sichuan Peoples R China

ISBN: (纸本)9783662456460;9783662456453

This paper proposes an improved algorithm based on minimizing the weighted error of mistake labels and miss labels in multi-label classification ensemble learning algorithm. The new algorithm aims to avoid local optimum by redefining weak classifiers. This algorithm considers the correlations of labels under the precondition of ensuring the error drops with the number of weak classifiers increasing. This paper proposes two improved approaches;one introduces combinational coefficients when combining weak classifiers, another smooth the weak classifier's output to avoid local optimum. We discuss the basis of these modifications, and verify the effectiveness of these algorithms. The experimental results show that all the improved algorithms are effective, and less prone to over fitting.

关键词： multi-label classification problem statistical learning ensemble learning adaboost algorithm confidence

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A Surveillance System for a Farm

A Surveillance System for a Farm

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International Conference on Informatics Engineering and Information Science (ICIEIS 2011)

作者： Kim, A-Ram Rhee, Sang-Yong Seok, Seung-Joon Lee, Hong-Chang Kim, Young-Baek Kyungnanm Univ Dept Comp Engn Gyeonnganm South Korea

ISBN: (纸本)9783642254826;9783642254833

This paper proposes a smart surveillance system to be able to identify person concerned or animal in order to prevent the crops stolen. Until now most of surveillance system use a method that records images by surveillance camera or sensor network. This kind of surveillance system has limitation not to identify person or not. The limitation bothers a farm supervisor. To overcome the problem, we detect moving object using codebook and distinguish whether to human or noise by using adaboost algorithm. Also, this system transmits image information to the supervisor. But even though detected object is person, it is not easily distinguishable whether person concerned or dubious one. That is why because of low resolution of images. To make unnecessary emergency alarm not ring, we adopt smart card technology.

关键词： Surveillance system Human identification adaboost algorithm

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Comparative Analysis of Various Face Detection Methods 2

Comparative Analysis of Various Face Detection Methods

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2nd IEEE-Pune-Section Annual International Conference (IEEE PuneCon)

作者： Ganakwar, Deepali G. Kadam, Vipulsangarm K. Dr Babasaheb Ambedkar Marathwada Univ Dept Engn & Technol Aurangabad Maharashtra India PES Coll Engn Dept Elect Engn Aurangabad Maharashtra India

ISBN: (纸本)9781728119243

with wide variety of increase in image and video database, the demand raises for automatic examination of this database as it is cumbersome in manual understanding and examination. This paper provides brief insights into some of renowned and mostly accepted Techniques of face detection. Face detection technique can be simply defined as a technology used by computer system that detects one or several human faces resulting in digital image. Recognizing and tracking the face, estimating pose and expressions, analysis of face and detecting any other features of face are the steps included in face detection method. Nowadays, face detection techniques owes one of the most active research areas of computer vision. Considering the face as an object that grabs countless applications in image processing makes it challenging task in computer vision. This paper provides a survey of existing literature on human face detection system. Three commonly used methods have been considered for comparative analysis in this paper.

关键词： Face detection integral image adaboost algorithm Hausdorff distance

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Face Detection System Based on Video Stream

Face Detection System Based on Video Stream

引用

International Conference on Computer Systems, Electronics and Control (ICCSEC)

作者： Zhang, Xingxian Liu, Chuanchang Su, Zhiyuan Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Beijing Univ Posts & Telecommun Sch Automat Beijing Peoples R China

ISBN: (纸本)9781538635735

With the development of electronic information and computer science technology, video capture becomes simpler and storage costs are rapidly declining, resulting in a dramatic increase in the amount of available video. In such circumstances, purely manual annotation and processing has been unable to deal with the massive video data. This has led to a growing demand for automated video analytics and interpretation technologies. The key underlying rationale for these video analytics applications is the automatic detection algorithm for video targets. In this paper, we analyze the common face detection algorithm and video streaming face detection applications. Combined with the actual situation, we design and implement a face detection system based on video streaming.

关键词： face detection face detecion in video adaboost algorithm support vector machines

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