Search results for: Medical image watermarking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2050

Search results for: Medical image watermarking

1060 Tumble Flow Analysis in an Unfired Engine Using Particle Image Velocimetry

Authors: B. Murali Krishna, J. M. Mallikarjuna

Abstract:

This paper deals with the experimental investigations of the in-cylinder tumble flows in an unfired internal combustion engine with a flat piston at the engine speeds ranging from 400 to 1000 rev/min., and also with the dome and dome-cavity pistons at an engine speed of 1000 rev/min., using particle image velocimetry. From the two-dimensional in-cylinder flow measurements, tumble flow analysis is carried out in the combustion space on a vertical plane passing through cylinder axis. To analyze the tumble flows, ensemble average velocity vectors are used and to characterize it, tumble ratio is estimated. From the results, generally, we have found that tumble ratio varies mainly with crank angle position. Also, at the end of compression stroke, average turbulent kinetic energy is more at higher engine speeds. We have also found that, at 330 crank angle position, flat piston shows an improvement of about 85 and 23% in tumble ratio, and about 24 and 2.5% in average turbulent kinetic energy compared to dome and dome-cavity pistons respectively

Keywords: In-cylinder flow, Dome piston, Cavity, Tumble, PIV

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1059 Real-time Target Tracking Using a Pan and Tilt Platform

Authors: Moulay A. Akhloufi

Abstract:

In recent years, we see an increase of interest for efficient tracking systems in surveillance applications. Many of the proposed techniques are designed for static cameras environments. When the camera is moving, tracking moving objects become more difficult and many techniques fail to detect and track the desired targets. The problem becomes more complex when we want to track a specific object in real-time using a moving Pan and Tilt camera system to keep the target within the image. This type of tracking is of high importance in surveillance applications. When a target is detected at a certain zone, the possibility of automatically tracking it continuously and keeping it within the image until action is taken is very important for security personnel working in very sensitive sites. This work presents a real-time tracking system permitting the detection and continuous tracking of targets using a Pan and Tilt camera platform. A novel and efficient approach for dealing with occlusions is presented. Also a new intelligent forget factor is introduced in order to take into account target shape variations and avoid learning non desired objects. Tests conducted in outdoor operational scenarios show the efficiency and robustness of the proposed approach.

Keywords: Tracking, surveillance, target detection, Pan and tilt.

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1058 Observations about the Principal Components Analysis and Data Clustering Techniques in the Study of Medical Data

Authors: Cristina G. Dascâlu, Corina Dima Cozma, Elena Carmen Cotrutz

Abstract:

The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.

Keywords: Data clustering, medical data, principal components analysis.

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1057 Experimental Technique for Vibration Reduction of a Motor Pumpin Medical Device

Authors: Young Kuen Cho, Dae Won Lee, Young-Jin Jung, Sung Kuk Kim, Dong-Hyun Seo, Chang-Yong Ko, Han Sung Kim

Abstract:

Many medical devices are driven by motor pumps. Some researchers reported that the vibration mainly affected medical devices using a motor pump. The purpose of this study was to examine the effect of stiffness and damping coefficient in a 3-dimensional (3D) model of a motor pump and spring. In the present paper, experimental and mathematical tests for the moments of inertia of the 3D model and the material properties were investigated by an INSTRON machine. The response surfaces could be generated by using 3D multi-body analysis and the design of experiment method. It showed that differences in contours of the response surface were clearly found for the particular area. Displacement of the center of the motor pump was decreased at K≈2000 N/M, C≈12.5 N-sec/M. However, the frequency was increased at K≈2000 N/M, C≈15 N-sec/M. In this study, this study suggested experimental technique for vibration reduction for a motor pump in medical device. The combined method suggested in this study will greatly contribute to design of medical devices concerning vibration and noise intervention.

Keywords: Motor pump, Spring, Vibration reduction, Medicaldevices, Moment of Inertia

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1056 Research on IBR-Driven Distributed Collaborative Visualization System

Authors: Yin Runmin, Song Changfeng

Abstract:

Image-based Rendering(IBR) techniques recently reached in broad fields which leads to a critical challenge to build up IBR-Driven visualization platform where meets requirement of high performance, large bounds of distributed visualization resource aggregation and concentration, multiple operators deploying and CSCW design employing. This paper presents an unique IBR-based visualization dataflow model refer to specific characters of IBR techniques and then discusses prominent feature of IBR-Driven distributed collaborative visualization (DCV) system before finally proposing an novel prototype. The prototype provides a well-defined three level modules especially work as Central Visualization Server, Local Proxy Server and Visualization Aid Environment, by which data and control for collaboration move through them followed the previous dataflow model. With aid of this triple hierarchy architecture of that, IBR oriented application construction turns to be easy. The employed augmented collaboration strategy not only achieve convenient multiple users synchronous control and stable processing management, but also is extendable and scalable.

Keywords: Image-Based Rendering, Distributed CollaborativeVisualization, Computer Supported Cooperative Work, Model andSimulation, Modular Visualization Environment.

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1055 A Novel Fuzzy-Neural Based Medical Diagnosis System

Authors: S. Moein, S. A. Monadjemi, P. Moallem

Abstract:

In this paper, application of artificial neural networks in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few hundreds cases was configured and applied to a MLP neural network. The results of the experiments and also the advantages of using a fuzzy approach were discussed as well. Outcomes suggest the role of effective symptoms selection and the advantages of data fuzzificaton on a neural networks-based automatic medical diagnosis system.

Keywords: Artificial Neural Networks, Fuzzy Logic, MedicalDiagnosis, Symptoms, Fuzzification.

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1054 Encryption Efficiency Analysis and Security Evaluation of RC6 Block Cipher for Digital Images

Authors: Hossam El-din H. Ahmed, Hamdy M. Kalash, Osama S. Farag Allah

Abstract:

This paper investigates the encryption efficiency of RC6 block cipher application to digital images, providing a new mathematical measure for encryption efficiency, which we will call the encryption quality instead of visual inspection, The encryption quality of RC6 block cipher is investigated among its several design parameters such as word size, number of rounds, and secret key length and the optimal choices for the best values of such design parameters are given. Also, the security analysis of RC6 block cipher for digital images is investigated from strict cryptographic viewpoint. The security estimations of RC6 block cipher for digital images against brute-force, statistical, and differential attacks are explored. Experiments are made to test the security of RC6 block cipher for digital images against all aforementioned types of attacks. Experiments and results verify and prove that RC6 block cipher is highly secure for real-time image encryption from cryptographic viewpoint. Thorough experimental tests are carried out with detailed analysis, demonstrating the high security of RC6 block cipher algorithm. So, RC6 block cipher can be considered to be a real-time secure symmetric encryption for digital images.

Keywords: Block cipher, Image encryption, Encryption quality, and Security analysis.

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1053 Hippocampus Segmentation using a Local Prior Model on its Boundary

Authors: Dimitrios Zarpalas, Anastasios Zafeiropoulos, Petros Daras, Nicos Maglaveras

Abstract:

Segmentation techniques based on Active Contour Models have been strongly benefited from the use of prior information during their evolution. Shape prior information is captured from a training set and is introduced in the optimization procedure to restrict the evolution into allowable shapes. In this way, the evolution converges onto regions even with weak boundaries. Although significant effort has been devoted on different ways of capturing and analyzing prior information, very little thought has been devoted on the way of combining image information with prior information. This paper focuses on a more natural way of incorporating the prior information in the level set framework. For proof of concept the method is applied on hippocampus segmentation in T1-MR images. Hippocampus segmentation is a very challenging task, due to the multivariate surrounding region and the missing boundary with the neighboring amygdala, whose intensities are identical. The proposed method, mimics the human segmentation way and thus shows enhancements in the segmentation accuracy.

Keywords: Medical imaging & processing, Brain MRI segmentation, hippocampus segmentation, hippocampus-amygdala missingboundary, weak boundary segmentation, region based segmentation, prior information, local weighting scheme in level sets, spatialdistribution of labels, gradient distribution on boundary.

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1052 Fast Search Method for Large Video Database Using Histogram Features and Temporal Division

Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

Abstract:

In this paper, we propose an improved fast search algorithm using combined histogram features and temporal division method for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal feature which is robust to color distortion. Combined with active search [4], a temporal pruning algorithm, fast and robust video search can be realized. The proposed search algorithm has been evaluated by 6 hours of video to search for given 200 MPEG video clips which each length is 30 seconds. Experimental results show the proposed algorithm can detect the similar video clip in merely 120ms, and Equal Error Rate (ERR) of 1% is achieved, which is more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, Adjacent pixel intensity differencequantization (APIDQ), DC image, Histogram feature.

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1051 A Novel Computer Vision Method for Evaluating Deformations of Fibers Cross Section in False Twist Textured Yarns

Authors: Dariush Semnani, Mehdi Ahangareianabhari, Hossein Ghayoor

Abstract:

In recent five decades, textured yarns of polyester fiber produced by false twist method are the most important and mass-produced manmade fibers. There are many parameters of cross section which affect the physical and mechanical properties of textured yarns. These parameters are surface area, perimeter, equivalent diameter, large diameter, small diameter, convexity, stiffness, eccentricity, and hydraulic diameter. These parameters were evaluated by digital image processing techniques. To find trends between production criteria and evaluated parameters of cross section, three criteria of production line have been adjusted and different types of yarns were produced. These criteria are temperature, drafting ratio, and D/Y ratio. Finally the relations between production criteria and cross section parameters were considered. The results showed that the presented technique can recognize and measure the parameters of fiber cross section in acceptable accuracy. Also, the optimum condition of adjustments has been estimated from results of image analysis evaluation.

Keywords: Computer Vision, Cross Section Analysis, Fibers Deformation, Textured Yarn

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1050 Development of Affordable and Reliable Diagnostic Tools to Record Vital Parameters for Improving Health Care in Low Resources Settings

Authors: Mannan Mridha, Usama Gazay, Kosovare V. Aslani, Hugo Linder, Alice Ravizza, Carmelo de Maria

Abstract:

In most developing countries, although the vast majority of the people are living in the rural areas, the qualified medical doctors are not available there. Health care workers and paramedics, called village doctors, informal healthcare providers, are largely responsible for the rural medical care. Mishaps due to wrong diagnosis and inappropriate medication have been causing serious suffering that is preventable. While innovators have created many devices, the vast majority of these technologies do not find applications to address the needs and conditions in low-resource settings. The primary motive is to address the acute lack of affordable medical technologies for the poor people in low-resource settings. A low cost smart medical device that is portable, battery operated and can be used at any point of care has been developed to detect breathing rate, electrocardiogram (ECG) and arterial pulse rate to improve diagnosis and monitoring of patients and thus improve care and safety. This simple and easy to use smart medical device can be used, managed and maintained effectively and safely by any health worker with some training. In order to empower the health workers and village doctors, our device is being further developed to integrate with ICT tools like smart phones and connect to the medical experts wherever available, to manage the serious health problems.

Keywords: Healthcare for low resources settings, health awareness education, improve patient care and safety, smart and affordable medical device.

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1049 Gait Biometric for Person Re-Identification

Authors: Lavanya Srinivasan

Abstract:

Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat and case recorded using long wave infrared, short wave infrared, medium wave infrared and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using You Only Look Once, background subtraction, silhouettes extraction and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the Principal Component Analysis and recognized using different classifiers. The comparative results with the different classifier show that Linear Discriminant Analysis outperform other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, You Only Look Once

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1048 Multiplayer Game System for Therapeutic Exercise in Which Players with Different Athletic Abilities Can Participate on an Even Competitive Footing

Authors: Kazumoto Tanaka, Takayuki Fujino

Abstract:

Sports games conducted as a group are a form of therapeutic exercise for aged people with decreased strength and for people suffering from permanent damage of stroke and other conditions. However, it is difficult for patients with different athletic abilities to play a game on an equal footing. This study specifically examines a computer video game designed for therapeutic exercise, and a game system with support given depending on athletic ability. Thereby, anyone playing the game can participate equally. This video-game, to be specific, is a popular variant of balloon volleyball, in which players hit a balloon by hand before it falls to the floor. In this game system, each player plays the game watching a monitor on which the system displays tailor-made video-game images adjusted to the person’s athletic ability, providing players with player-adaptive assist support. We have developed a multiplayer game system with an image generation technique for the tailor-made video-game and conducted tests to evaluate it.

Keywords: Therapeutic exercise, computer video game, disability-adaptive assist, tailor-made video-game image.

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1047 Classroom Incivility Behaviours among Medical Students: A Comparative Study in Pakistan

Authors: Manal Rauf

Abstract:

Trained medical practitioners are produced from medical colleges serving in public and private sectors. Prime responsibility of teaching faculty is to inculcate required work ethic among the students by serving as role models for them. It is an observed fact that classroom incivility behaviours are providing a friction in achieving these targets. Present study aimed at identification of classroom incivility behaviours observed by teachers and students of public and private medical colleges as per Glasser’s Choice Theory, making a comparison and investigating the strategies being adopted by teachers of both sectors to control undesired class room behaviours. Findings revealed that a significant difference occurs between teacher and student incivility behaviours. Public sector teacher focussed on survival as a strong factor behind in civil behaviours whereas private sector teachers considered power as the precedent for incivility. Teachers of both sectors are required to use verbal as well as non-verbal immediacy to reach a healthy leaning environment.

Keywords: Classroom incivility behaviour, Glasser choice theory, Mehrabian immediacy theory, medical student.

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1046 Smartphone Photography in Urban China

Authors: Wen Zhang

Abstract:

The smartphone plays a significant role in media convergence, and smartphone photography is reconstructing the way we communicate and think. This article aims to explore the smartphone photography practices of urban Chinese smartphone users and images produced by smartphones from a techno-cultural perspective. The analysis consists of two types of data: One is a semi-structured interview of 21 participants, and the other consists of the images created by the participants. The findings are organised in two parts. The first part summarises the current tendencies of capturing, editing, sharing and archiving digital images via smartphones. The second part shows that food and selfie/anti-selfie are the preferred subjects of smartphone photographic images from a technical and multi-purpose perspective and demonstrates that screenshots and image texts are new genres of non-photographic images that are frequently made by smartphones, which contributes to improving operational efficiency, disseminating information and sharing knowledge. The analyses illustrate the positive impacts between smartphones and photography enthusiasm and practices based on the diffusion of innovation theory, which also makes us rethink the value of photographs and the practice of ‘photographic seeing’ from the screen itself.

Keywords: Digital photography, photographic-seeing, media convergence, technological innovation, smartphone, selfie/anti-selfie, image-text.

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1045 Use of Item Response Theory in Medical Surgical Nursing Achievement Examination

Authors: Rita C. Ramos

Abstract:

Medical Surgical Nursing is one of the major subjects in nursing. This study examined the validity and reliability of the achievement examination utilizing the Classical Test Theory and Item Response Theory. The study answered the following objectives specifically : ( a) To establish the validity and reliability of the achievement examination utilizing Classical Test Theory and Item Response Theory ; ( b ) To determine the dimensionality measure of items and ( c ) to compare the item difficulty and item discrimination of the Medical Surgical Nursing Achievement examination using Classical Test Theory ( CTT ) and Item Response Theory ( IRT ). The developed instrument was administered to fourth year nursing students (N= 136) of a private university in Manila. The findings yielded the following results: The achievement examination is reliable both using CTT and IRT. The findings indicate person and item statistics from two frameworks are quite alike. The achievement examination formed a unidimensional construct.

Keywords: Achievement Examination, Item Response Theory, Medical Surgical, Nursing.

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1044 Statistical Distributions of the Lapped Transform Coefficients for Images

Authors: Vijay Kumar Nath, Deepika Hazarika, Anil Mahanta,

Abstract:

Discrete Cosine Transform (DCT) based transform coding is very popular in image, video and speech compression due to its good energy compaction and decorrelating properties. However, at low bit rates, the reconstructed images generally suffer from visually annoying blocking artifacts as a result of coarse quantization. Lapped transform was proposed as an alternative to the DCT with reduced blocking artifacts and increased coding gain. Lapped transforms are popular for their good performance, robustness against oversmoothing and availability of fast implementation algorithms. However, there is no proper study reported in the literature regarding the statistical distributions of block Lapped Orthogonal Transform (LOT) and Lapped Biorthogonal Transform (LBT) coefficients. This study performs two goodness-of-fit tests, the Kolmogorov-Smirnov (KS) test and the 2- test, to determine the distribution that best fits the LOT and LBT coefficients. The experimental results show that the distribution of a majority of the significant AC coefficients can be modeled by the Generalized Gaussian distribution. The knowledge of the statistical distribution of transform coefficients greatly helps in the design of optimal quantizers that may lead to minimum distortion and hence achieve optimal coding efficiency.

Keywords: Lapped orthogonal transform, Lapped biorthogonal transform, Image compression, KS test,

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1043 The Influence of Fiber Volume Fraction on Thermal Conductivity of Pultruded Profile

Authors: V. Lukášová, P. Peukert, V. Votrubec

Abstract:

Thermal conductivity in the x, y and z-directions was measured on a pultruded profile that was manufactured by the technology of pulling from glass fibers and a polyester matrix. The results of measurements of thermal conductivity showed considerable variability in different directions. The caused variability in thermal conductivity was expected due fraction variations. The cross-section of the pultruded profile was scanned. An image analysis illustrated an uneven distribution of the fibers and the matrix in the cross-section. The distribution of these inequalities was processed into a Voronoi diagram in the observed area of the pultruded profile cross-section. In order to verify whether the variation of the fiber volume fraction in the pultruded profile can affect its thermal conductivity, the numerical simulations in the ANSYS Fluent were performed. The simulation was based on the geometry reconstructed from image analysis. The aim is to quantify thermal conductivity numerically. Above all, images with different volume fractions were chosen. The results of the measured thermal conductivity were compared with the calculated thermal conductivity. The evaluated data proved a strong correlation between volume fraction and thermal conductivity of the pultruded profile. Based on presented results, a modification of production technology may be proposed.

Keywords: Numerical simulation, pultruded profile, volume fraction, thermal conductivity.

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1042 Image Transmission in Low-Power Networks in Mobile Communications Channel

Authors: M. A. M. El-Bendary, H. Kazimian, A. E. Abo-El-azm, N. A. El-Fishawy, F. El-Samie, F. Shawki

Abstract:

This paper studies a vital issue in wireless communications, which is the transmission of images over Wireless Personal Area Networks (WPANs) through the Bluetooth network. It presents a simple method to improve the efficiency of error control code of old Bluetooth versions over mobile WPANs through Interleaved Error Control Code (IECC) technique. The encoded packets are interleaved by simple block interleaver. Also, the paper presents a chaotic interleaving scheme as a tool against bursts of errors which depends on the chaotic Baker map. Also, the paper proposes using the chaotic interleaver instead of traditional block interleaver with Forward Error Control (FEC) scheme. A comparison study between the proposed and standard techniques for image transmission over a correlated fading channel is presented. Simulation results reveal the superiority of the proposed chaotic interleaving scheme to other schemes. Also, the superiority of FEC with proposed chaotic interleaver to the conventional interleavers with enhancing the security level with chaotic interleaving packetby- packet basis.

Keywords: Mobile Bluetooth terminals, WPANs, Jackes' model, Interleaving technique, chaotic interleaver

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1041 Problem Based Learning in B. P. Koirala Institute of Health Sciences

Authors: Gurung S., Yadav B. N., Budhathoki SS.

Abstract:

Problem based learning is one of the highly acclaimed learning methods in medical education since its first introduction at Mc-Master University in Canada in the 1960s. It has now been adopted as a teaching learning method in many medical colleges of Nepal. B.P. Koirala Institute of Health Sciences (BPKIHS), a health science deemed university is the second institute in Nepal to establish problem-based learning academic program and need-based teaching approach hence minimizing teaching through lectures since its inception. During the first two years of MBBS course, the curriculum is divided into various organ-systems incorporated with problem-based learning exercise each of one week duration.

Keywords: PBL, medical education.

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1040 Fish Locomotion for Innovative Marine Propulsion Systems

Authors: Omar B. Yaakob, Yasser M. Ahmed, Ahmad F. Said

Abstract:

There is an essential need for obtaining the mathematical representation of fish body undulations, which can be used for designing and building new innovative types of marine propulsion systems with less environmental impact. This research work presents a case study to derive the mathematical model for fish body movement. Observation and capturing image methods were used in this study in order to obtain a mathematical representation of Clariasbatrachus fish (catfish). An experiment was conducted by using an aquarium with dimension 0.609 m x 0.304 m x 0.304 m, and a 0.5 m ruler was attached at the base of the aquarium. Progressive Scan Monochrome Camera was positioned at 1.8 m above the base of the aquarium to provide swimming sequences. Seven points were marked on the fish body using white marker to indicate the fish movement and measuring the amplitude of undulation. Images from video recordings (20 frames/s) were analyzed frame by frame using local coordinate system, with time interval 0.05 s. The amplitudes of undulations were obtained for image analysis from each point that has been marked on fish body. A graph of amplitude of undulations versus time was plotted by using computer to derive a mathematical fit. The function for the graph is polynomial with nine orders.

Keywords: Fish locomotion, body undulation, steady and unsteady swimming modes.

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1039 Attention Based Fully Convolutional Neural Network for Simultaneous Detection and Segmentation of Optic Disc in Retinal Fundus Images

Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

Abstract:

Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: Ocular diseases, retinal fundus image, optic disc detection and segmentation, fully convolutional network, overlap measure.

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1038 Analysis of Message Authentication in Turbo Coded Halftoned Images using Exit Charts

Authors: Andhe Dharani, P. S. Satyanarayana, Andhe Pallavi

Abstract:

Considering payload, reliability, security and operational lifetime as major constraints in transmission of images we put forward in this paper a steganographic technique implemented at the physical layer. We suggest transmission of Halftoned images (payload constraint) in wireless sensor networks to reduce the amount of transmitted data. For low power and interference limited applications Turbo codes provide suitable reliability. Ensuring security is one of the highest priorities in many sensor networks. The Turbo Code structure apart from providing forward error correction can be utilized to provide for encryption. We first consider the Halftoned image and then the method of embedding a block of data (called secret) in this Halftoned image during the turbo encoding process is presented. The small modifications required at the turbo decoder end to extract the embedded data are presented next. The implementation complexity and the degradation of the BER (bit error rate) in the Turbo based stego system are analyzed. Using some of the entropy based crypt analytic techniques we show that the strength of our Turbo based stego system approaches that found in the OTPs (one time pad).

Keywords: Halftoning, Turbo codes, security, operationallifetime, Turbo based stego system.

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1037 Matching-Based Cercospora Leaf Spot Detection in Sugar Beet

Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu

Abstract:

In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.

Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).

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1036 A Real-time Computer Vision System for VehicleTracking and Collision Detection

Authors: Mustafa Kisa, Fatih Mehmet Botsali

Abstract:

Recent developments in automotive technology are focused on economy, comfort and safety. Vehicle tracking and collision detection systems are attracting attention of many investigators focused on safety of driving in the field of automotive mechatronics. In this paper, a vision-based vehicle detection system is presented. Developed system is intended to be used in collision detection and driver alert. The system uses RGB images captured by a camera in a car driven in the highway. Images captured by the moving camera are used to detect the moving vehicles in the image. A vehicle ahead of the camera is detected in daylight conditions. The proposed method detects moving vehicles by subtracting successive images. Plate height of the vehicle is determined by using a plate recognition algorithm. Distance of the moving object is calculated by using the plate height. After determination of the distance of the moving vehicle relative speed of the vehicle and Time-to-Collision are calculated by using distances measured in successive images. Results obtained in road tests are discussed in order to validate the use of the proposed method.

Keywords: Image possessing, vehicle tracking, license plate detection, computer vision.

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1035 A Computer Aided Detection (CAD) System for Microcalcifications in Mammograms - MammoScan mCaD

Authors: Kjersti Engan, Thor Ole Gulsrud, Karl Fredrik Fretheim, Barbro Furebotten Iversen, Liv Eriksen

Abstract:

Clusters of microcalcifications in mammograms are an important sign of breast cancer. This paper presents a complete Computer Aided Detection (CAD) scheme for automatic detection of clustered microcalcifications in digital mammograms. The proposed system, MammoScan μCaD, consists of three main steps. Firstly all potential microcalcifications are detected using a a method for feature extraction, VarMet, and adaptive thresholding. This will also give a number of false detections. The goal of the second step, Classifier level 1, is to remove everything but microcalcifications. The last step, Classifier level 2, uses learned dictionaries and sparse representations as a texture classification technique to distinguish single, benign microcalcifications from clustered microcalcifications, in addition to remove some remaining false detections. The system is trained and tested on true digital data from Stavanger University Hospital, and the results are evaluated by radiologists. The overall results are promising, with a sensitivity > 90 % and a low false detection rate (approx 1 unwanted pr. image, or 0.3 false pr. image).

Keywords: mammogram, microcalcifications, detection, CAD, MammoScan μCaD, VarMet, dictionary learning, texture, FTCM, classification, adaptive thresholding

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1034 Tagged Grid Matching Based Object Detection in Wavelet Neural Network

Authors: R. Arulmurugan, P. Sengottuvelan

Abstract:

Object detection using Wavelet Neural Network (WNN) plays a major contribution in the analysis of image processing. Existing cluster-based algorithm for co-saliency object detection performs the work on the multiple images. The co-saliency detection results are not desirable to handle the multi scale image objects in WNN. Existing Super Resolution (SR) scheme for landmark images identifies the corresponding regions in the images and reduces the mismatching rate. But the Structure-aware matching criterion is not paying attention to detect multiple regions in SR images and fail to enhance the result percentage of object detection. To detect the objects in the high-resolution remote sensing images, Tagged Grid Matching (TGM) technique is proposed in this paper. TGM technique consists of the three main components such as object determination, object searching and object verification in WNN. Initially, object determination in TGM technique specifies the position and size of objects in the current image. The specification of the position and size using the hierarchical grid easily determines the multiple objects. Second component, object searching in TGM technique is carried out using the cross-point searching. The cross out searching point of the objects is selected to faster the searching process and reduces the detection time. Final component performs the object verification process in TGM technique for identifying (i.e.,) detecting the dissimilarity of objects in the current frame. The verification process matches the search result grid points with the stored grid points to easily detect the objects using the Gabor wavelet Transform. The implementation of TGM technique offers a significant improvement on the multi-object detection rate, processing time, precision factor and detection accuracy level.

Keywords: Object Detection, Cross-point Searching, Wavelet Neural Network, Object Determination, Gabor Wavelet Transform, Tagged Grid Matching.

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1033 Optical Fish Tracking in Fishways using Neural Networks

Authors: Alvaro Rodriguez, Maria Bermudez, Juan R. Rabuñal, Jeronimo Puertas

Abstract:

One of the main issues in Computer Vision is to extract the movement of one or several points or objects of interest in an image or video sequence to conduct any kind of study or control process. Different techniques to solve this problem have been applied in numerous areas such as surveillance systems, analysis of traffic, motion capture, image compression, navigation systems and others, where the specific characteristics of each scenario determine the approximation to the problem. This paper puts forward a Computer Vision based algorithm to analyze fish trajectories in high turbulence conditions in artificial structures called vertical slot fishways, designed to allow the upstream migration of fish through obstructions in rivers. The suggested algorithm calculates the position of the fish at every instant starting from images recorded with a camera and using neural networks to execute fish detection on images. Different laboratory tests have been carried out in a full scale fishway model and with living fishes, allowing the reconstruction of the fish trajectory and the measurement of velocities and accelerations of the fish. These data can provide useful information to design more effective vertical slot fishways.

Keywords: Computer Vision, Neural Network, Fishway, Fish Trajectory, Tracking

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1032 Retrospective Synthetic Focusing with Correlation Weighting for Very High Frame Rate Ultrasound

Authors: Chang-Lin Hu, Yao-You Cheng, Meng-Lin Li

Abstract:

The need of high frame-rate imaging has been triggered by the new applications of ultrasound imaging to transient elastography and real-time 3D ultrasound. Using plane wave excitation (PWE) is one of the methods to achieve very high frame-rate imaging since an image can be formed with a single insonification. However, due to the lack of transmit focusing, the image quality with PWE is lower compared with those using conventional focused transmission. To solve this problem, we propose a filter-retrieved transmit focusing (FRF) technique combined with cross-correlation weighting (FRF+CC weighting) for high frame-rate imaging with PWE. A restrospective focusing filter is designed to simultaneously minimize the predefined sidelobe energy associated with single PWE and the filter energy related to the signal-to-noise-ratio (SNR). This filter attempts to maintain the mainlobe signals and to reduce the sidelobe ones, which gives similar mainlobe signals and different sidelobes between the original PWE and the FRF baseband data. Normalized cross-correlation coefficient at zero lag is calculated to quantify the degree of similarity at each imaging point and used as a weighting matrix to the FRF baseband data to further suppress sidelobes, thus improving the filter-retrieved focusing quality.

Keywords: retrospective synthetic focusing, high frame rate, correlation weighting.

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1031 Weakened Vortex Shedding from a Rotating Cylinder

Authors: Sharul S. Dol

Abstract:

An experimental study of the turbulent near wake of a rotating circular cylinder was made at a Reynolds number of 2000 for velocity ratios, λ between 0 and 2.7. Particle image velocimetry data are analyzed to study the effects of rotation on the flow structures behind the cylinder. The results indicate that the rotation of the cylinder causes significant changes in the vortex formation. Kármán vortex shedding pattern of alternating vortices gives rise to strong periodic fluctuations of a vortex street for λ < 2.0. Alternate vortex shedding is weak and close to being suppressed at λ = 2.0 resulting a distorted street with vortices of alternating sense subsequently being found on opposite sides. Only part of the circulation is shed due to the interference in the separation point, mixing in the base region, re-attachment, and vortex cut-off phenomenon. Alternating vortex shedding pattern diminishes and completely disappears when the velocity ratio is 2.7. The shed vortices are insignificant in size and forming a single line of vortex street. It is clear that flow asymmetries will deteriorate vortex shedding, and when the asymmetries are large enough, total inhibition of a periodic street occurs.

Keywords: Circulation, particle image velocimetry, rotating circular cylinder, smoke-wire flow visualization, Strouhal number, vortex shedding, vortex street.

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