Search results for: images about Japan and Japanese people
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9774

Search results for: images about Japan and Japanese people

9474 A Decision Support System to Detect the Lumbar Disc Disease on the Basis of Clinical MRI

Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

Abstract:

In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

Procedia PDF Downloads 501
9473 Selecting the Best Sub-Region Indexing the Images in the Case of Weak Segmentation Based on Local Color Histograms

Authors: Mawloud Mosbah, Bachir Boucheham

Abstract:

Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, color global histogram, color local histogram, weak segmentation, Euclidean distance

Procedia PDF Downloads 346
9472 Prediction, Production, and Comprehension: Exploring the Influence of Salience in Language Processing

Authors: Andy H. Clark

Abstract:

This research looks into the relationship between language comprehension and production with a specific focus on the role of salience in shaping these processes. Salience, our most immediate perception of what is most probable out of all possible situations and outcomes strongly affects our perception and action in language production and comprehension. This study investigates the impact of geographic and emotional attachments to the target language on the differences in the learners’ comprehension and production abilities. Using quantitative research methods (Qualtrics, SPSS), this study examines preferential choices of two groups of Japanese English language learners: those residing in the United States and those in Japan. By comparing and contrasting these two groups, we hope to gain a better understanding of how salience of linguistics cues influences language processing.

Keywords: intercultural pragmatics, salience, production, comprehension, pragmatics, action, perception, cognition

Procedia PDF Downloads 50
9471 The Modeling of City Bus Fuel Economy during the JE05 Emission Test Cycle

Authors: Miroslaw Wendeker, Piotr Kacejko, Marcin Szlachetka, Mariusz Duk

Abstract:

This paper discusses a model of fuel economy in a city bus driving in a dynamic urban environment. Rapid changes in speed result in a constantly changing kinetic energy accumulated in a bus mass and an increased fuel consumption due to hardly recuperated kinetic energy. The model is based on the bench test results achieved from chassis dynamometer, airport and city street researches. The verified model was applied to simulate the behavior of a bus during the Japanese JE05 Emission Test Cycle. The fuel consumption was calculated for three separate research stages, i.e. urban, downtown and motorway. The simulations were performed for several values of vehicle mass and electrical load applied to on-board devices. The research results show fuel consumption is impacted by driving dynamics.

Keywords: city bus, heavy duty vehicle, Japanese JE05 test cycle, kinetic energy

Procedia PDF Downloads 292
9470 2D Convolutional Networks for Automatic Segmentation of Knee Cartilage in 3D MRI

Authors: Ananya Ananya, Karthik Rao

Abstract:

Accurate segmentation of knee cartilage in 3-D magnetic resonance (MR) images for quantitative assessment of volume is crucial for studying and diagnosing osteoarthritis (OA) of the knee, one of the major causes of disability in elderly people. Radiologists generally perform this task in slice-by-slice manner taking 15-20 minutes per 3D image, and lead to high inter and intra observer variability. Hence automatic methods for knee cartilage segmentation are desirable and are an active field of research. This paper presents design and experimental evaluation of 2D convolutional neural networks based fully automated methods for knee cartilage segmentation in 3D MRI. The architectures are validated based on 40 test images and 60 training images from SKI10 dataset. The proposed methods segment 2D slices one by one, which are then combined to give segmentation for whole 3D images. Proposed methods are modified versions of U-net and dilated convolutions, consisting of a single step that segments the given image to 5 labels: background, femoral cartilage, tibia cartilage, femoral bone and tibia bone; cartilages being the primary components of interest. U-net consists of a contracting path and an expanding path, to capture context and localization respectively. Dilated convolutions lead to an exponential expansion of receptive field with only a linear increase in a number of parameters. A combination of modified U-net and dilated convolutions has also been explored. These architectures segment one 3D image in 8 – 10 seconds giving average volumetric Dice Score Coefficients (DSC) of 0.950 - 0.962 for femoral cartilage and 0.951 - 0.966 for tibia cartilage, reference being the manual segmentation.

Keywords: convolutional neural networks, dilated convolutions, 3 dimensional, fully automated, knee cartilage, MRI, segmentation, U-net

Procedia PDF Downloads 242
9469 Maritime English Communication Training for Japanese VTS Operators in the Congested Area Including the Narrow Channel of Akashi Strait

Authors: Kenji Tanaka, Kazumi Sugita, Yuto Mizushima

Abstract:

This paper introduces a noteworthy form of English communication training for the officers and operators of the Osaka-Bay Marine Traffic Information Service (Osaka MARTIS) of the Japan Coast Guard working in the congested area at the Akashi Strait in Hyogo Prefecture, Japan. The authors of this paper, Marine Technical College’s (MTC) English language instructors, have been holding about forty lectures and exercises in basic and normal Maritime English (ME) for several groups of MARTIS personnel at Osaka MARTIS annually since they started the training in 2005. Trainees are expected to be qualified Maritime Third-Class Radio Operators who are responsible for providing safety information to a daily average of seven to eight hundred vessels that pass through the Akashi Strait, one of Japan’s narrowest channels. As of 2022, the instructors are conducting 55 remote lessons at MARTIS. One lesson is 90 minutes long. All 26 trainees are given oral and written assessments. The trainees need to pass the examination to become qualified operators every year, requiring them to train and maintain their linguistic levels even during the pandemic of Corona Virus Disease-19 (COVID-19). The vessel traffic information provided by Osaka MARTIS in Maritime English language is essential to the work involving the use of very high frequency (VHF) communication between MARTIS and vessels in the area. ME is the common language mainly used on board merchant, fishing, and recreational vessels, normally at sea. ME was edited and recommended by the International Maritime Organization in the 1970s, was revised in 2002, and has undergone continual revision. The vessel’s circumstances are much more serious at the strait than those at the open sea, so these vessels need ME to receive guidance from the center when passing through the narrow strait. The imminent and challenging situations at the strait necessitate that textbooks’ contents include the basics of the phrase book for seafarers as well as specific and additional navigational information, pronunciation exercises, notes on keywords and phrases, explanations about collocations, sample sentences, and explanations about the differences between synonyms especially those focusing on terminologies necessary for passing through the strait. Additionally, short Japanese-English translation quizzes about these topics, as well as prescribed readings about the maritime sector, are include in the textbook. All of these exercises have been trained in the remote education system since the outbreak of COVID-19. According to the guidelines of ME edited in 2009, the lowest level necessary for seafarers is B1 (lower individual users) of The Common European Framework of Reference for Languages: Learning, Teaching, Assessment (CEFR). Therefore, this vocational ME language training at Osaka MARTIS aims for its trainees to communicate at levels higher than B1. A noteworthy proof of improvement from this training is that most of the trainees have become qualified marine radio communication officers.

Keywords: akashi strait, B1 of CEFR, maritime english communication training, osaka martis

Procedia PDF Downloads 107
9468 Verification and Proposal of Information Processing Model Using EEG-Based Brain Activity Monitoring

Authors: Toshitaka Higashino, Naoki Wakamiya

Abstract:

Human beings perform a task by perceiving information from outside, recognizing them, and responding them. There have been various attempts to analyze and understand internal processes behind the reaction to a given stimulus by conducting psychological experiments and analysis from multiple perspectives. Among these, we focused on Model Human Processor (MHP). However, it was built based on psychological experiments and thus the relation with brain activity was unclear so far. To verify the validity of the MHP and propose our model from a viewpoint of neuroscience, EEG (Electroencephalography) measurements are performed during experiments in this study. More specifically, first, experiments were conducted where Latin alphabet characters were used as visual stimuli. In addition to response time, ERPs (event-related potentials) such as N100 and P300 were measured by using EEG. By comparing cycle time predicted by the MHP and latency of ERPs, it was found that N100, related to perception of stimuli, appeared at the end of the perceptual processor. Furthermore, by conducting an additional experiment, it was revealed that P300, related to decision making, appeared during the response decision process, not at the end. Second, by experiments using Japanese Hiragana characters, i.e. Japan's own phonetic symbols, those findings were confirmed. Finally, Japanese Kanji characters were used as more complicated visual stimuli. A Kanji character usually has several readings and several meanings. Despite the difference, a reading-related task and a meaning-related task exhibited similar results, meaning that they involved similar information processing processes of the brain. Based on those results, our model was proposed which reflects response time and ERP latency. It consists of three processors: the perception processor from an input of a stimulus to appearance of N100, the cognitive processor from N100 to P300, and the decision-action processor from P300 to response. Using our model, an application system which reflects brain activity can be established.

Keywords: brain activity, EEG, information processing model, model human processor

Procedia PDF Downloads 88
9467 Identifying Self-Disclosure in Indonesian Reality Show: A Comprehensive Study

Authors: Dwi Ashari

Abstract:

This study attempts to disclose people’s privacy in Indonesian media. Many television (henceforth: TV) programs have shown the exposure of people’s privacy. People, not only celebrities, who appear in TV program often, share their life to the participants to get very intimate self-disclosure with them. Indonesia, as one of the countries with highest population, has many people who watch television everyday. This can be the major factor for some TV stations to create a program to get people’s attention to gain more profit. This study examines some factors of Indonesia TV programs that share the people’s privacy. The relation of privacy in Indonesia TV programs will be related to the concept of self-disclosure and intimacy between the people who share and watch the programs.

Keywords: Indonesia, media, privacy, self-disclosure

Procedia PDF Downloads 317
9466 Efficacy of Self-Assessment in Written Production among High School Students

Authors: Yoko Suganuma Oi

Abstract:

The purpose of the present study is to find the efficacy of high school student self-assessment of written production. It aimed to explore the following two research questions: 1)How is topic development of their written production improved after student self-assessment and teacher feedback? 2)Does the consistency between student self-assessment and teacher assessment develop after student self-assessment and teacher feedback? The data came from the written production of 82 Japanese high school students aged from 16 to 18 years old, an American English teacher and one Japanese English teacher. Students were asked to write English compositions, about 150 words, for thirty minutes without using dictionaries. It was conducted twice at intervals of two months. Students were supposed to assess their own compositions by themselves. Teachers also assessed students’ compositions using the same assessment sheet. The results showed that both teachers and students assessed the second compositions higher than the first compositions. However, there was not the development of the consistency in coherence.

Keywords: feedback, self-assessment, topic development, high school students

Procedia PDF Downloads 489
9465 A New Approach to Image Stitching of Radiographic Images

Authors: Somaya Adwan, Rasha Majed, Lamya'a Majed, Hamzah Arof

Abstract:

In order to produce images with whole body parts, X-ray of different portions of the body parts is assembled using image stitching methods. A new method for image stitching that exploits mutually feature based method and direct based method to identify and merge pairs of X-ray medical images is presented in this paper. The performance of the proposed method based on this hybrid approach is investigated in this paper. The ability of the proposed method to stitch and merge the overlapping pairs of images is demonstrated. Our proposed method display comparable if not superior performance to other feature based methods that are mentioned in the literature on the standard databases. These results are promising and demonstrate the potential of the proposed method for further development to tackle more advanced stitching problems.

Keywords: image stitching, direct based method, panoramic image, X-ray

Procedia PDF Downloads 523
9464 Iterative Reconstruction Techniques as a Dose Reduction Tool in Pediatric Computed Tomography Imaging: A Phantom Study

Authors: Ajit Brindhaban

Abstract:

Background and Purpose: Computed Tomography (CT) scans have become the largest source of radiation in radiological imaging. The purpose of this study was to compare the quality of pediatric Computed Tomography (CT) images reconstructed using Filtered Back Projection (FBP) with images reconstructed using different strengths of Iterative Reconstruction (IR) technique, and to perform a feasibility study to assess the use of IR techniques as a dose reduction tool. Materials and Methods: An anthropomorphic phantom representing a 5-year old child was scanned, in two stages, using a Siemens Somatom CT unit. In stage one, scans of the head, chest and abdomen were performed using standard protocols recommended by the scanner manufacturer. Images were reconstructed using FBP and 5 different strengths of IR. Contrast-to-Noise Ratios (CNR) were calculated from average CT number and its standard deviation measured in regions of interest created in the lungs, bone, and soft tissues regions of the phantom. Paired t-test and the one-way ANOVA were used to compare the CNR from FBP images with IR images, at p = 0.05 level. The lowest strength value of IR that produced the highest CNR was identified. In the second stage, scans of the head was performed with decreased mA(s) values relative to the increase in CNR compared to the standard FBP protocol. CNR values were compared in this stage using Paired t-test at p = 0.05 level. Results: Images reconstructed using IR technique had higher CNR values (p < 0.01.) in all regions compared to the FBP images, at all strengths of IR. The CNR increased with increasing IR strength of up to 3, in the head and chest images. Increases beyond this strength were insignificant. In abdomen images, CNR continued to increase up to strength 5. The results also indicated that, IR techniques improve CNR by a up to factor of 1.5. Based on the CNR values at strength 3 of IR images and CNR values of FBP images, a reduction in mA(s) of about 20% was identified. The images of the head acquired at 20% reduced mA(s) and reconstructed using IR at strength 3, had similar CNR as FBP images at standard mA(s). In the head scans of the phantom used in this study, it was demonstrated that similar CNR can be achieved even when the mA(s) is reduced by about 20% if IR technique with strength of 3 is used for reconstruction. Conclusions: The IR technique produced better image quality at all strengths of IR in comparison to FBP. IR technique can provide approximately 20% dose reduction in pediatric head CT while maintaining the same image quality as FBP technique.

Keywords: filtered back projection, image quality, iterative reconstruction, pediatric computed tomography imaging

Procedia PDF Downloads 130
9463 Estimation and Restoration of Ill-Posed Parameters for Underwater Motion Blurred Images

Authors: M. Vimal Raj, S. Sakthivel Murugan

Abstract:

Underwater images degrade their quality due to atmospheric conditions. One of the major problems in an underwater image is motion blur caused by the imaging device or the movement of the object. In order to rectify that in post-imaging, parameters of the blurred image are to be estimated. So, the point spread function is estimated by the properties, using the spectrum of the image. To improve the estimation accuracy of the parameters, Optimized Polynomial Lagrange Interpolation (OPLI) method is implemented after the angle and length measurement of motion-blurred images. Initially, the data were collected from real-time environments in Chennai and processed. The proposed OPLI method shows better accuracy than the existing classical Cepstral, Hough, and Radon transform estimation methods for underwater images.

Keywords: image restoration, motion blur, parameter estimation, radon transform, underwater

Procedia PDF Downloads 162
9462 Different Cognitive Processes in Selecting Spatial Demonstratives: A Cross-Linguistic Experimental Survey

Authors: Yusuke Sugaya

Abstract:

Our research conducts a cross-linguistic experimental investigation into the cognitive processes involved in distance judgment necessary for selecting demonstratives in deictic usage. Speakers may consider the addressee's judgment or apply certain criteria for distance judgment when they produce demonstratives. While it can be assumed that there are language and cultural differences, it remains unclear how these differences manifest across languages. This research conducted online experiments involving speakers of six languages—Japanese, Spanish, Irish, English, Italian, and French—in which a wide variety of drawings were presented on a screen, varying conditions from three perspectives: addressee, comparisons, and standard. The results of the experiments revealed various distinct features associated with demonstratives in each language, highlighting differences from a comparative standpoint. For one thing, there was an influence of a specific reference point (i.e., Standard) on the selection in Japanese and Spanish, whereas there was relatively an influence of competitors in English and Italian.

Keywords: demonstratives, cross-linguistic experiment, distance judgment, social cognition

Procedia PDF Downloads 22
9461 Predictive Functional Control with Disturbance Observer for Tendon-Driven Balloon Actuator

Authors: Jun-ya Nagase, Toshiyuki Satoh, Norihiko Saga, Koichi Suzumori

Abstract:

In recent years, Japanese society has been aging, engendering a labour shortage of young workers. Robots are therefore expected to perform tasks such as rehabilitation, nursing elderly people, and day-to-day work support for elderly people. The pneumatic balloon actuator is a rubber artificial muscle developed for use in a robot hand in such environments. This actuator has a long stroke, and a high power-to-weight ratio compared with the present pneumatic artificial muscle. Moreover, the dynamic characteristics of this actuator resemble those of human muscle. This study evaluated characteristics of force control of balloon actuator using a predictive functional control (PFC) system with disturbance observer. The predictive functional control is a model-based predictive control (MPC) scheme that predicts the future outputs of the actual plants over the prediction horizon and computes the control effort over the control horizon at every sampling instance. For this study, a 1-link finger system using a pneumatic balloon actuator is developed. Then experiments of PFC control with disturbance observer are performed. These experiments demonstrate the feasibility of its control of a pneumatic balloon actuator for a robot hand.

Keywords: disturbance observer, pneumatic balloon, predictive functional control, rubber artificial muscle

Procedia PDF Downloads 434
9460 Seismic Reinforcement of Existing Japanese Wooden Houses Using Folded Exterior Thin Steel Plates

Authors: Jiro Takagi

Abstract:

Approximately 90 percent of the casualties in the near-fault-type Kobe earthquake in 1995 resulted from the collapse of wooden houses, although a limited number of collapses of this type of building were reported in the more recent off-shore-type Tohoku Earthquake in 2011 (excluding direct damage by the Tsunami). Kumamoto earthquake in 2016 also revealed the vulnerability of old wooden houses in Japan. There are approximately 24.5 million wooden houses in Japan and roughly 40 percent of them are considered to have the inadequate seismic-resisting capacity. Therefore, seismic strengthening of these wooden houses is an urgent task. However, it has not been quickly done for various reasons, including cost and inconvenience during the reinforcing work. Residents typically spend their money on improvements that more directly affect their daily housing environment (such as interior renovation, equipment renewal, and placement of thermal insulation) rather than on strengthening against extremely rare events such as large earthquakes. Considering this tendency of residents, a new approach to developing a seismic strengthening method for wooden houses is needed. The seismic reinforcement method developed in this research uses folded galvanized thin steel plates as both shear walls and the new exterior architectural finish. The existing finish is not removed. Because galvanized steel plates are aesthetic and durable, they are commonly used in modern Japanese buildings on roofs and walls. Residents could feel a physical change through the reinforcement, covering existing exterior walls with steel plates. Also, this exterior reinforcement can be installed with only outdoor work, thereby reducing inconvenience for residents since they would not be required to move out temporarily during construction. The Durability of the exterior is enhanced, and the reinforcing work can be done efficiently since perfect water protection is not required for the new finish. In this method, the entire exterior surface would function as shear walls and thus the pull-out force induced by seismic lateral load would be significantly reduced as compared with a typical reinforcement scheme of adding braces in selected frames. Consequently, reinforcing details of anchors to the foundations would be less difficult. In order to attach the exterior galvanized thin steel plates to the houses, new wooden beams are placed next to the existing beams. In this research, steel connections between the existing and new beams are developed, which contain a gap for the existing finish between the two beams. The thin steel plates are screwed to the new beams and the connecting vertical members. The seismic-resisting performance of the shear walls with thin steel plates is experimentally verified both for the frames and connections. It is confirmed that the performance is high enough for bracing general wooden houses.

Keywords: experiment, seismic reinforcement, thin steel plates, wooden houses

Procedia PDF Downloads 210
9459 Principle Component Analysis on Colon Cancer Detection

Authors: N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Rita Magdalena, R. D. Atmaja, Sofia Saidah, Ocky Tiaramukti

Abstract:

Colon cancer or colorectal cancer is a type of cancer that attacks the last part of the human digestive system. Lymphoma and carcinoma are types of cancer that attack human’s colon. Colon cancer causes deaths about half a million people every year. In Indonesia, colon cancer is the third largest cancer case for women and second in men. Unhealthy lifestyles such as minimum consumption of fiber, rarely exercising and lack of awareness for early detection are factors that cause high cases of colon cancer. The aim of this project is to produce a system that can detect and classify images into type of colon cancer lymphoma, carcinoma, or normal. The designed system used 198 data colon cancer tissue pathology, consist of 66 images for Lymphoma cancer, 66 images for carcinoma cancer and 66 for normal / healthy colon condition. This system will classify colon cancer starting from image preprocessing, feature extraction using Principal Component Analysis (PCA) and classification using K-Nearest Neighbor (K-NN) method. Several stages in preprocessing are resize, convert RGB image to grayscale, edge detection and last, histogram equalization. Tests will be done by trying some K-NN input parameter setting. The result of this project is an image processing system that can detect and classify the type of colon cancer with high accuracy and low computation time.

Keywords: carcinoma, colorectal cancer, k-nearest neighbor, lymphoma, principle component analysis

Procedia PDF Downloads 191
9458 Content-Based Mammograms Retrieval Based on Breast Density Criteria Using Bidimensional Empirical Mode Decomposition

Authors: Sourour Khouaja, Hejer Jlassi, Nadia Feddaoui, Kamel Hamrouni

Abstract:

Most medical images, and especially mammographies, are now stored in large databases. Retrieving a desired image is considered of great importance in order to find previous similar cases diagnosis. Our method is implemented to assist radiologists in retrieving mammographic images containing breast with similar density aspect as seen on the mammogram. This is becoming a challenge seeing the importance of density criteria in cancer provision and its effect on segmentation issues. We used the BEMD (Bidimensional Empirical Mode Decomposition) to characterize the content of images and Euclidean distance measure similarity between images. Through the experiments on the MIAS mammography image database, we confirm that the results are promising. The performance was evaluated using precision and recall curves comparing query and retrieved images. Computing recall-precision proved the effectiveness of applying the CBIR in the large mammographic image databases. We found a precision of 91.2% for mammography with a recall of 86.8%.

Keywords: BEMD, breast density, contend-based, image retrieval, mammography

Procedia PDF Downloads 215
9457 Quality Assurance in Cardiac Disorder Detection Images

Authors: Anam Naveed, Asma Andleeb, Mehreen Sirshar

Abstract:

In the article, Image processing techniques have been applied on cardiac images for enhancing the image quality. Two types of methodologies considers for survey, invasive techniques and non-invasive techniques. Different image processes for improvement of cardiac image quality and reduce the amount of radiation exposure for invasive techniques are explored. Different image processing algorithms for enhancing the noninvasive cardiac image qualities are described. Beside these two methodologies, third methodology has applied on live streaming of heart rate on ECG window for extracting necessary information, removing noise and enhancing quality. Sensitivity analyses have been carried out to investigate the impacts of cardiac images for diagnosis of cardiac arteries disease and how the enhancement on images will help the cardiologist to diagnoses disease. The paper evaluates strengths and weaknesses of different techniques applied for improved the image quality and draw a conclusion. Some specific limitations must be considered for whole survey, like the patient heart beat must be 70-75 beats/minute while doing the angiography, similarly patient weight and exposure radiation amount has some limitation.

Keywords: cardiac images, CT angiography, critical analysis, exposure radiation, invasive techniques, invasive techniques, non-invasive techniques

Procedia PDF Downloads 325
9456 Water Detection in Aerial Images Using Fuzzy Sets

Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

Abstract:

This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

Procedia PDF Downloads 454
9455 Underwater Image Enhancement and Reconstruction Using CNN and the MultiUNet Model

Authors: Snehal G. Teli, R. J. Shelke

Abstract:

CNN and MultiUNet models are the framework for the proposed method for enhancing and reconstructing underwater images. Multiscale merging of features and regeneration are both performed by the MultiUNet. CNN collects relevant features. Extensive tests on benchmark datasets show that the proposed strategy performs better than the latest methods. As a result of this work, underwater images can be represented and interpreted in a number of underwater applications with greater clarity. This strategy will advance underwater exploration and marine research by enhancing real-time underwater image processing systems, underwater robotic vision, and underwater surveillance.

Keywords: convolutional neural network, image enhancement, machine learning, multiunet, underwater images

Procedia PDF Downloads 56
9454 Approach Based on Fuzzy C-Means for Band Selection in Hyperspectral Images

Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

Abstract:

Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: band selection, fuzzy c-means, k-means, hyperspectral image

Procedia PDF Downloads 380
9453 Significance of Archetypal Sounds: Exploring Mystical Practices of Uttarakhand Himalayas

Authors: Vineet Gairola

Abstract:

In many cultures, ethnographers have tried to set up a tight link between music and possession. However, they rarely informed us about the psychology of interactions between music and the possessed. Ancient myths and the archetypal find expression through the rituals practiced in Uttarakhand. In Uttarakhand (a part of the Central Himalayan region), an intriguing archetypal healing mechanism takes place. Some people get 'possessed' by a deity and shower blessings onto people gathered for a puja in a temple, where invocation of deity takes place through two archetypal drumming instruments played together named dhol-damaun. There is devi-doli (palanquin of the goddess) worship, which is carried on the shoulders of two people and is said to be tilting and shaking on its own. Archetypal in the modern mind survives effortlessly. The 'oceanic' of religious feelings are explored through an oral text of Dholsagar. The method of ethnography along with case-studies has been used. A substantial part of fieldwork was carried out in Rudraprayag, Uttarakhand. The research suggests that the collective unconscious is also sonic in nature, which is characterized by sounds and rhythms—not only symbols and images, as Dr. Jung suggested.

Keywords: archetypal, music, myth, mysticism, possession, sonic collective unconscious

Procedia PDF Downloads 109
9452 Binarization and Recognition of Characters from Historical Degraded Documents

Authors: Bency Jacob, S.B. Waykar

Abstract:

Degradations in historical document images appear due to aging of the documents. It is very difficult to understand and retrieve text from badly degraded documents as there is variation between the document foreground and background. Thresholding of such document images either result in broken characters or detection of false texts. Numerous algorithms exist that can separate text and background efficiently in the textual regions of the document; but portions of background are mistaken as text in areas that hardly contain any text. This paper presents a way to overcome these problems by a robust binarization technique that recovers the text from a severely degraded document images and thereby increases the accuracy of optical character recognition systems. The proposed document recovery algorithm efficiently removes degradations from document images. Here we are using the ostus method ,local thresholding and global thresholding and after the binarization training and recognizing the characters in the degraded documents.

Keywords: binarization, denoising, global thresholding, local thresholding, thresholding

Procedia PDF Downloads 328
9451 Bipolar Impulse Noise Removal and Edge Preservation in Color Images and Video Using Improved Kuwahara Filter

Authors: Reji Thankachan, Varsha PS

Abstract:

Both image capturing devices and human visual systems are nonlinear. Hence nonlinear filtering methods outperforms its linear counterpart in many applications. Linear methods are unable to remove impulsive noise in images by preserving its edges and fine details. In addition, linear algorithms are unable to remove signal dependent or multiplicative noise in images. This paper presents an approach to denoise and smoothen the Bipolar impulse noised images and videos using improved Kuwahara filter. It involves a 2 stage algorithm which includes a noise detection followed by filtering. Numerous simulation demonstrate that proposed method outperforms the existing method by eliminating the painting like flattening effect along the local feature direction while preserving edge with improvement in PSNR and MSE.

Keywords: bipolar impulse noise, Kuwahara, PSNR MSE, PDF

Procedia PDF Downloads 482
9450 Investigating the Editing's Effect of Advertising Photos on the Virtual Purchase Decision Based on the Quantitative Electroencephalogram (EEG) Parameters

Authors: Parya Tabei, Maryam Habibifar

Abstract:

Decision-making is an important cognitive function that can be defined as the process of choosing an option among available options to achieve a specific goal. Consumer ‘need’ is the main reason for purchasing decisions. Human decision-making while buying products online is subject to various factors, one of which is the quality and effect of advertising photos. Advertising photo editing can have a significant impact on people's virtual purchase decisions. This technique helps improve the quality and overall appearance of photos by adjusting various aspects such as brightness, contrast, colors, cropping, resizing, and adding filters. This study, by examining the effect of editing advertising photos on the virtual purchase decision using EEG data, tries to investigate the effect of edited images on the decision-making of customers. A group of 30 participants were asked to react to 24 edited and unedited images while their EEG was recorded. Analysis of the EEG data revealed increased alpha wave activity in the occipital regions (O1, O2) for both edited and unedited images, which is related to visual processing and attention. Additionally, there was an increase in beta wave activity in the frontal regions (FP1, FP2, F4, F8) when participants viewed edited images, suggesting involvement in cognitive processes such as decision-making and evaluating advertising content. Gamma wave activity also increased in various regions, especially the frontal and parietal regions, which are associated with higher cognitive functions, such as attention, memory, and perception, when viewing the edited images. While the visual processing reflected by alpha waves remained consistent across different visual conditions, editing advertising photos appeared to boost neural activity in frontal and parietal regions associated with decision-making processes. These Findings suggest that photo editing could potentially influence consumer perceptions during virtual shopping experiences by modulating brain activity related to product assessment and purchase decisions.

Keywords: virtual purchase decision, advertising photo, EEG parameters, decision Making

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9449 The Role of the Founding Ideals of a University in Higher Education

Authors: Masanori Kimura

Abstract:

The “founding spirit” of a Japanese university is similar to the mission statement of a Western university, but the difference between the two is that the former more closely reflects the founder’s inner world because it usually originates from the strong personal beliefs that the founder held when establishing the university. To find how much this ideology actually valued in today’s higher education, this paper surveys 2091 job openings for foreign language full-time faculty positions, posted by Japanese private universities from 2012 to 2016. The results suggest that women’s universities and universities with religious affiliations have a tendency to request that successful candidates observe their founding spirit, or at least demonstrate some understanding of the ideology after being hired. On the other hand, co-ed universities and universities with no religious affiliations do not show such a distinct tendency. A chi-square test revealed that this difference between the two groups was statistically significant (p<.01). Furthermore, the paper argues that it is not always appropriate for universities to evaluate themselves based on a single evaluation scale such as university rankings, and that both faculty and staff members need to be more aware of the founding spirit to improve the quality of the education the university provides.

Keywords: founding spirit, higher education, university administrative management, university evaluation

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9448 Genomic Identification of Anisakis Simplex Larvae by PCR-RAPD

Authors: Fumiko Kojima, Shuji Fujimoto

Abstract:

Anisakiasis is a disease caused by infection with an anisakid larvae, mostly Anisakis simplex. The larvae commonly infect in marine fish and the disease is frequently reported in areas of the world where fish is consumed raw, lightly pickled or salted. In Japan, people have the habit of eating raw fish such as ‘sushi’ or ‘sashimi’, so they have more chance of infection with larvae of anisakid nematodes. There are three sibling species in A. simplex larvae, namely, A. simplex sensu stricto (Asss), A. pegreffii (Ap) and A. simplex C. It was revealed that Ap is dominant among the larvae from fish (Scomber japonics) in the Japan Sea side and Asss is dominant among those of the Pacific Ocean side conversely. Although anisakiasis has happened in Japan among both the Japan Sea side area and the Pacific Ocean side area. The aim of this study was to investigate genetic variations between the siblings (Asss and Ap) and within the same sibling species by random amplified polymorphic DNA (RAPD) technique. In order to investigate the genetic difference among the each A. simplex larvae, we used RAPD technique to differentiate individuals of A. simplex obtained from Scomber japonics fish those were caught in the Japan sea (Goto Islands in Nagasaki Prefecture) and the cost of Pacific Ocean (Kanagawa Prefecture). The RAPD patterns of the control DNA (Genus Raphidascaris) were markedly different from those of the A. simplex. There were differences in amplification patterns between Asss and Ap. The RAPD patterns for larvae obtained from fish of the same sea were somewhat different and variations were detected even among larvae from the same fish. These results suggest the considerable high genetic variability between Asss and Ap and the possible existence of genetic variation within the sibling species.

Keywords: Anisakiasis in Japan, Anisakis simplex, genomic identification, PCR-RAPD

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9447 Segmentation of the Liver and Spleen From Abdominal CT Images Using Watershed Approach

Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

Abstract:

The phase of segmentation is an important step in the processing and interpretation of medical images. In this paper, we focus on the segmentation of liver and spleen from the abdomen computed tomography (CT) images. The importance of our study comes from the fact that the segmentation of ROI from CT images is usually a difficult task. This difficulty is the gray’s level of which is similar to the other organ also the ROI are connected to the ribs, heart, kidneys, etc. Our proposed method is based on the anatomical information and mathematical morphology tools used in the image processing field. At first, we try to remove the surrounding and connected organs and tissues by applying morphological filters. This first step makes the extraction of interest regions easier. The second step consists of improving the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce these deficiencies by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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9446 Privacy Policy Prediction for Uploaded Image on Content Sharing Sites

Authors: Pallavi Mane, Nikita Mankar, Shraddha Mazire, Rasika Pashankar

Abstract:

Content sharing sites are very useful in sharing information and images. However, with the increasing demand of content sharing sites privacy and security concern have also increased. There is need to develop a tool for controlling user access to their shared content. Therefore, we are developing an Adaptive Privacy Policy Prediction (A3P) system which is helpful for users to create privacy settings for their images. We propose the two-level framework which assigns the best available privacy policy for the users images according to users available histories on the site.

Keywords: online information services, prediction, security and protection, web based services

Procedia PDF Downloads 339
9445 Traffic Density Measurement by Automatic Detection of the Vehicles Using Gradient Vectors from Aerial Images

Authors: Saman Ghaffarian, Ilgin Gökaşar

Abstract:

This paper presents a new automatic vehicle detection method from very high resolution aerial images to measure traffic density. The proposed method starts by extracting road regions from image using road vector data. Then, the road image is divided into equal sections considering resolution of the images. Gradient vectors of the road image are computed from edge map of the corresponding image. Gradient vectors on the each boundary of the sections are divided where the gradient vectors significantly change their directions. Finally, number of vehicles in each section is carried out by calculating the standard deviation of the gradient vectors in each group and accepting the group as vehicle that has standard deviation above predefined threshold value. The proposed method was tested in four very high resolution aerial images acquired from Istanbul, Turkey which illustrate roads and vehicles with diverse characteristics. The results show the reliability of the proposed method in detecting vehicles by producing 86% overall F1 accuracy value.

Keywords: aerial images, intelligent transportation systems, traffic density measurement, vehicle detection

Procedia PDF Downloads 363