Search results for: image recognition

Authors: Katalin Szöllősi, László Szabó

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Introduction and purpose: Even though female sexual dysfunctions are common among women in the postpartum period, the profile of these disturbances has not been well investigated in Hungary yet. The aim of the study was to evaluate the postpartum female sexual functions in Hungary. This research sought to investigate the possible predictor factors which can influence postpartum female sexual functions. Method and sample: This was a cross-sectional study, including patients from two maternity clinics in Budapest. 113 women were recruited into our study 3 months after their childbirth. 53 had vaginal birth, 60 had a caesarian section. Data were collected from medical reports in addition by using self-developed questions and validated questionnaires in order to measure important predictors which may be responsible for postpartum sexual dysfunctions such as mode of delivery, parity, urinary incontinence and body image. Sexual functions were evaluated by the Hungarian version of the Female Sexual Function Index (FSFI). The Hungarian version of Body Image Questionnaire-Short Form14 (BSQ-SF14) was applied for assessing body image. Results: 82,3% of the participants began to have sexual intercourse within three months postpartum. 53,98% of the participants reported sexual dysfunctions (cut-off FSFI score 26,55). According to our results mode of delivery, parity, hemorrhoids, time of intercourse, resumption was not associated with female sexual dysfunctions. We found correlation at a tendential level between urinary incontinence and sexual dysfunctions (p=0,003, R=0,26). We found a negative correlation at a tendential level between the total score of BSQ-SF14 and FSFI (p=0,03, R=-0,269). Only 32,74% of women reported discussing sexual life with health care professionals. However, 67,25% of them would have had the need to be asked about their postpartum health issues. Conclusions and recommendations: The prevalence of female sexual dysfunctions were relatively high after childbirth. We found that incontinence and body image was associated with sexual dysfunctions; other risk factors remained unknown. Despite regular contact with health care professionals, women rarely get any information about postpartum sexual health issues. The high prevalence of dysfunctions indicates the need for further investigation to address other risk factors and proper counselling of women after childbirth.

Keywords: body image, postpartum, sexual dysfunction, urinary incontinence

Procedia PDF Downloads 109

Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

Procedia PDF Downloads 245

Authors: Simeon Mayala, Ida Herdlevær, Jonas Bull Haugsøen, Shamundeeswari Anandan, Sonia Gavasso, Morten Brun

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In this paper, we propose a minimum spanning tree-based method for segmenting brain tumors. The proposed method performs interactive segmentation based on the minimum spanning tree without tuning parameters. The steps involve preprocessing, making a graph, constructing a minimum spanning tree, and a newly implemented way of interactively segmenting the region of interest. In the preprocessing step, a Gaussian filter is applied to 2D images to remove the noise. Then, the pixel neighbor graph is weighted by intensity differences and the corresponding minimum spanning tree is constructed. The image is loaded in an interactive window for segmenting the tumor. The region of interest and the background are selected by clicking to split the minimum spanning tree into two trees. One of these trees represents the region of interest and the other represents the background. Finally, the segmentation given by the two trees is visualized. The proposed method was tested by segmenting two different 2D brain T1-weighted magnetic resonance image data sets. The comparison between our results and the standard gold segmentation confirmed the validity of the minimum spanning tree approach. The proposed method is simple to implement and the results indicate that it is accurate and efficient.

Keywords: brain tumor, brain tumor segmentation, minimum spanning tree, segmentation, image processing

Procedia PDF Downloads 117

Authors: Nabilah Ibrahim, Hafiz Mohd Zaini, Wan Fatin Liyana Mutalib

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Ultrasound equipment or machine is capable to scan in two dimensional (2D) areas. However there are some limitations occur during scanning an object. The problem will occur when scanning process that involving the asymmetric object. In this project, the ultrasound probe holder for asymmetric reflector scanning in 3D image is proposed to make easier for scanning the phantom or object that has asymmetric shape. Initially, the constructed asymmetric phantom that construct will be used in 2D scanning. Next, the asymmetric phantom will be interfaced by the movement of ultrasound probe holder using the Arduino software. After that, the performance of the ultrasound probe holder will be evaluated by using the various asymmetric reflector or phantom in constructing a 3D image

Keywords: ultrasound 3D images, axial and lateral resolution, asymmetric reflector, Arduino software

Procedia PDF Downloads 556

Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Brighton Chamunorwa

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The current remote sensing of water quality procedures does not provide a step representing physical visualisation of the monitored dam. The application of the remote sensing of water quality techniques may benefit from use of mathematical morphology operators for shape identification. Given an input of dam outline, morphological operators such as the hit or miss transform identifies if the water body is present on input remotely sensed images. This study seeks to determine the accuracy of the hit or miss transform to identify dams monitored by the water resources authorities in South Africa on satellite images. To achieve this objective the study download a Landsat image acquired in winter and tested the capability of the hit or miss transform using shapefile boundaries of dams in the crocodile marico catchment. The results of the experiment show that it is possible to detect most dams on the Landsat image after the adjusting the erosion operator to detect pixel matching a percentage similarity of 80% and above. Successfully implementation of the current study contributes towards optimisation of mathematical morphology image operators. Additionally, the effort helps develop remote sensing of water quality monitoring with improved simulation of the conventional procedures.

Keywords: hit or miss transform, mathematical morphology, remote sensing, water quality monitoring

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Authors: Seane Mabitsela

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The Territory of Namibia was entrusted to South Africa as a Mandate under the League of Nations Covenant. After the dissolution of the League of Nations and the commencement of United Nations operations, South Africa's conception of its legal obligations under the mandate varied from those of other members of the United Nations. Because of that, the General Assembly requested the International Court of Justice for an Advisory Opinion on the international obligations of South Africa arising therefrom. The International Court of Justice declared that South West Africa was still a mandatory territory under the Covenant of the League of Nations. It also held that South Africa continued to transmit petitions from inhabitants of the territory, the supervisory functions to be exercised by the United Nations, to which the annual reports and the petitions were to be submitted. Subject to this judgement, the question of South West Africa remained a dispute relating to the mandate brought before the International Court of Justice against South Africa. The International Court of Justice and South Africa dispute reflected the nature of the Namibian inhabitants’ appeal for recognition at the United Nations.

Keywords: International Court of Justice, Namibia, petitions, United Nations

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: P. Gil, F. Charrua-Santos, A. A. Baptista, S. Azevedo, A. Espirito-Santo, J. Páscoa

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Lean manufacturing is a philosophy of industrial management that aims to identify and eliminate any waste that exists in the companies. The augmented reality is a new technology that stills being developed in terms of software and hardware. This technology consists of an image capture device, a device for data processing and an image visualization equipment to visualize collected and processed images. It is characterized by being a technology that merges the reality with the virtual environment, so there is an instantaneous interaction between the two environments. The present work intends to demonstrate that the use of the augmented reality will contribute to improve some tools and methods used in Lean manufacturing philosophy. Through several examples of application in industry it will be demonstrated that the technological impact of the augmented reality on the Lean Manufacturing philosophy contribute to added value improvements.

Keywords: lean manufacturing, augmented reality, case studies, value

Procedia PDF Downloads 621

Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Mahdi Salarian, Xi Xu, Rashid Ansari

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Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database. This paper proposes an efficient method for limiting the search space for image retrieval engine by extracting and leveraging additional media information about Estimated Positional Error (EP E) to address complexity and accuracy issues in the search, especially to be used for compensating GPS location inaccuracy in dense urban areas. The improved performance is achieved by up to a hundred-fold reduction in the search area used in available reference methods while providing improved accuracy. To test our procedure we created a database by acquiring Google Street View (GSV) images for down town of Chicago. Other available databases are not suitable for our approach due to lack of EP E for the query images. We tested the procedure using more than 200 query images along with EP E acquired mostly in the densest areas of Chicago with different phones and in different conditions such as low illumination and from under rail tracks. The effectiveness of our approach and the effect of size and sector angle of the search area are discussed and experimental results demonstrate how our proposed method can improve performance just by utilizing a data that is available for mobile systems such as smart phones.

Keywords: localization, retrieval, GPS uncertainty, bag of word

Procedia PDF Downloads 282

Authors: Li-Kai Kuo, Shyh-Hau Wang

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The kinetic trajectory of the median nerve (MN) in the wrist has shown to be capable of being applied to assess the carpal tunnel syndrome (CTS), and was found able to be detected by high-frequency ultrasound image via motion tracking technique. Yet, previous study may not quickly perform the measurement due to the use of a single element transducer for ultrasound image scanning. Therefore, previous system is not appropriate for being applied to clinical application. In the present study, B-mode ultrasound images of the wrist corresponding to movements of fingers from flexion to extension were acquired by clinical applicable real-time scanner. The kinetic trajectories of MN were off-line estimated utilizing two dimensional Baysian speckle tracking (TDBST) technique. The experiments were carried out from ten volunteers by ultrasound scanner at 12 MHz frequency. Results verified from phantom experiments have demonstrated that TDBST technique is able to detect the movement of MN based on signals of the past and present information and then to reduce the computational complications associated with the effect of such image quality as the resolution and contrast variations. Moreover, TDBST technique tended to be more accurate than that of the normalized cross correlation tracking (NCCT) technique used in previous study to detect movements of the MN in the wrist. In response to fingers’ flexion movement, the kinetic trajectory of the MN moved toward the ulnar-palmar direction, and then toward the radial-dorsal direction corresponding to the extensional movement. TDBST technique and the employed ultrasound image scanner have verified to be feasible to sensitively detect the kinetic trajectory and displacement of the MN. It thus could be further applied to diagnose CTS clinically and to improve the measurements to assess 3D trajectory of the MN.

Keywords: baysian speckle tracking, carpal tunnel syndrome, median nerve, motion tracking

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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In this paper, a set of Filipino Phonetically Balanced Word list consisting of 250 words (PBW250) were constructed for a phoneme-level ASR system for the Filipino language. The Entropy Maximization is used to obtain phonological balance in the list. Entropy of phonemes in a word is maximized, providing an optimal balance in each word’s phonological distribution using the Add-Delete Method (PBW algorithm) and is compared to the modified PBW algorithm implemented in a dynamic algorithm approach to obtain optimization. The gained entropy score of 4.2791 and 4.2902 for the PBW and modified algorithm respectively. The PBW250 was recorded by 40 respondents, each with 2 sets data. Recordings from 30 respondents were trained to produce an acoustic model that were tested using recordings from 10 respondents using the HMM Toolkit (HTK). The results of test gave the maximum accuracy rate of 97.77% for a speaker dependent test and 89.36% for a speaker independent test.

Keywords: entropy maximization, Filipino language, Hidden Markov Model, phonetically balanced words, speech recognition

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Authors: André Augusto Ceballos Melo

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Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

Procedia PDF Downloads 134

Authors: B. G. Abiona, O. E. Fapojuwo, T. Akinlawon

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This study assessed the influence of human resource management practices on agricultural employees’ behavior. Data were collected from 75 randomly selected respondents using a well-structured questionnaire. The mean age of the employees’ was 43.2 years. Major human resource management practices that influence employees behaviors were: In-service training are given to employees on a regular basis (average value of x=3.44), management reward employees who are committed to their job (average value of x =3.41) and reward are designed to encourage wide participation and activity (average value of x=3.41). Also, major employees’ behavior include: Managers and employees’ wants to create better job performance (average value of x=3.13) and administrator provides praise and recognition for effective performance and show appreciation for special effort (average value of x=3.05). Major factors affecting employees’ behavior were: inadequate training (average value of x=2.93), inadequate local and international training (average value of x=2.87), inadequate grants for training programmes (average value of x= 2.81). A significant relationship was found between gender (χ2 = 37.204, P<0.05), educational qualification (χ2 = 59.093, P<0.05), income (r =0.122, P<0.05) and human resource management practices (r = 0.573, P< 0.05) of the respondents and employees’ behavior. Management should encourage employees who are committed to their job through awards and recognition.

Keywords: human resources management, agricultural employees, behaviour research institutes, Nigeria

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Authors: Jianghe Niu, Mu-Qing Huang

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This research applies qualitative approach to conduct literature review to explore and analyze the relationship between three pairs of female Chinese public figure with high levels of education and social recognitionto understand the role of male admiration in driving hostile response from the female pairs. Commonalities in the cases were found. Hong Huang and SuMang, both are coaches in the Chinese fashion industry, and their contemporaries are also editors-in-chief of major fashion publications. Lin Huiyin and XieBingxin are successful women in the field of literature and architecture. They are of similar age and share similar place of origin and family background; the former received high levels of male admiration, while the latter did not. Zhang Ailing and Su Qing, they are both highly established in the field of literature with very similar style, and they shared great admiration for each other’s talent once upon a time. Zhang’s husband used to be Su Qing's lover, and it was only through Su Qing that He met Zhang Ailing. Conclusion: The relationship between Chinese women, especially women with high levels of education and social recognition, the degree of similarities, and the closeness of relationship of these attributes (such as age, family background, education level, peer similarity, appearance, family, marriage) is positively correlated with increased level of discord, hostility, and hostility. This is observed across the three samples. The relationship between Chinese women, especially women with high levels of education and social recognition - if there are men romantically involved and the levels of male admiration is not equal between the two females - the imbalance of male admiration will act as a leverage that further drives up the levels of negative relationship between the women. This is the case with the first two examples above. The relationship between Chinese women, especially women with high levels of education and social recognition - if there is a man romantically involved and if he’s a previous lover to one woman - the transfer of male romantic interest from the first women to the second women, the new union will bring the hostile and negative relationship with the two females to a peak.

Keywords: Chinese, gender, relationship, women

Procedia PDF Downloads 118

Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng

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Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).

Keywords: motion detection, motion tracking, trajectory analysis, video surveillance

Procedia PDF Downloads 544

Authors: Guorong Sui, Xingwei Jia, Fei Tong, Xiumin Gao

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Camera calibration is a fundamental issue of high precision noncontact measurement. And it is necessary to analyze and study the reliability and application range of its linear model which is often used in the camera calibration. According to the imaging features of monocular cameras, a camera model which is based on the image pixel coordinates and three dimensional space coordinates is built. Using our own customized template, the image pixel coordinate is obtained by the subpixel corner detection method. Without considering the aberration of the optical system, the feature extraction and linearity analysis of the line segment in the template are performed. Moreover, the experiment is repeated 11 times by constantly varying the measuring distance. At last, the linearity of the camera is achieved by fitting 11 groups of data. The camera model measurement results show that the relative error does not exceed 1%, and the repeated measurement error is not more than 0.1 mm magnitude. Meanwhile, it is found that the model has some measurement differences in the different region and object distance. The experiment results show this linear model is simple and practical, and have good linearity within a certain object distance. These experiment results provide a powerful basis for establishment of the linear model of camera. These works will have potential value to the actual engineering measurement.

Keywords: camera linear model, geometric imaging relationship, image pixel coordinates, three dimensional space coordinates, sub-pixel corner detection

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Authors: Sabri Serkan Gulluoglu

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It is possible with Geographic Information Systems (GIS) that the information about all natural and artificial resources on the earth is obtained taking advantage of satellite images are obtained by remote sensing techniques. However, determination of unknown sources, mapping of the distribution and efficient evaluation of resources are defined may not be possible with the original image. For this reasons, some process steps are needed like transformation, pre-processing, image enhancement and classification to provide the most accurate assessment numerically and visually. Many studies which present the phases of obtaining and processing of the satellite images have examined in the literature study. The research showed that the determination of the process steps may be followed at this subject with the existence of a common whole may provide to progress the process rapidly for the necessary and possible studies which will be.

Keywords: remote sensing, satellite imaging, gis, computer science, information

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Authors: Joshi Manisha, Shivaram, Anand Vinekar, Tanya Susan Mathews, Yeshaswini Nagaraj

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Retinopathy of prematurity (ROP) is abnormal blood vessel development in the retina of the eye in a premature infant. The principal object of the invention is to provide a technique for detecting demarcation line and ridge detection for a given ROP image that facilitates early detection of ROP in stage 1 and stage 2. The demarcation line is an indicator of Stage 1 of the ROP and the ridge is the hallmark of typically Stage 2 ROP. Thirty Retcam images of Asian Indian infants obtained during routine ROP screening have been used for the analysis. A graphical user interface has been developed to detect demarcation line/ridge and to extract ground truth. This novel algorithm uses multilevel vessel enhancement to enhance tubular structures in the digital ROP images. It has been observed that the orientation of the demarcation line/ridge is normal to the direction of the blood vessels, which is used for the identification of the ridge/ demarcation line. Quantitative analysis has been presented based on gold standard images marked by expert ophthalmologist. Image based analysis has been based on the length and the position of the detected ridge. In image based evaluation, average sensitivity and positive predictive value was found to be 92.30% and 85.71% respectively. In pixel based evaluation, average sensitivity, specificity, positive predictive value and negative predictive value achieved were 60.38%, 99.66%, 52.77% and 99.75% respectively.

Keywords: ROP, ridge, multilevel vessel enhancement, biomedical

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Authors: L. K. Akila

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Art activities can fund as a clinical support tool (CST) between interventions in Art Therapy to direct the client back towards better outcome goals. In the present study, during free art sessions, researcher examined the possibilities of motivating the adolescent group to involve in art making process by reflecting upon art intervention administered. Results show that adolescents’ reflecting upon their art works generated during the intervention; could change their perceptions and cognitions to improve their positive approach by restructuring their art expressions. Consequently, such reflections triggered and improved their emotions, feelings and ideas, and produced secure attachment between family, peers and teachers. By the end of interference, transformations experienced were effective more upon depression, self-image, and self-efficacy, and to a certain extent on aggressive patterns represented.

Keywords: adolescent, adolescent psychology, aggression, art, art therapy, cognition, depression, emotion, self-image

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Authors: Chih-Chung Huang, Po-Hsun Peng

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Ultrasound transient elastography has become a valuable tool for many clinical diagnoses, such as liver diseases and breast cancer. The pathological tissue can be distinguished by elastography due to its stiffness is different from surrounding normal tissues. An ultrafast frame rate of ultrasound imaging is needed for transient elastography modality. The elastography obtained in the ultrafast system suffers from a low quality for resolution, and affects the robustness of the transient elastography. In order to overcome these problems, a coherent plane wave compounding technique has been proposed for conventional ultrasound system which the operating frequency is around 3-15 MHz. The purpose of this study is to develop a novel beamforming technique for high frequency ultrasound coherent plane-wave compounding imaging and the simulated results will provide the standards for hardware developments. Plane-wave compounding imaging produces a series of low-resolution images, which fires whole elements of an array transducer in one shot with different inclination angles and receives the echoes by conventional beamforming, and compounds them coherently. Simulations of plane-wave compounding image and focused transmit image were performed using Field II. All images were produced by point spread functions (PSFs) and cyst phantoms with a 64-element linear array working at 35MHz center frequency, 55% bandwidth, and pitch of 0.05 mm. The F number is 1.55 in all the simulations. The simulated results of PSFs and cyst phantom which were obtained using single, 17, 43 angles plane wave transmission (angle of each plane wave is separated by 0.75 degree), and focused transmission. The resolution and contrast of image were improved with the number of angles of firing plane wave. The lateral resolutions for different methods were measured by -10 dB lateral beam width. Comparison of the plane-wave compounding image and focused transmit image, both images exhibited the same lateral resolution of 70 um as 37 angles were performed. The lateral resolution can reach 55 um as the plane-wave was compounded 47 angles. All the results show the potential of using high-frequency plane-wave compound imaging for realizing the elastic properties of the microstructure tissue, such as eye, skin and vessel walls in the future.

Keywords: plane wave imaging, high frequency ultrasound, elastography, beamforming

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Authors: Nirjhar Dhang, S. Vinay Kumar

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Concrete is a non-homogeneous mix of coarse aggregates, sand, cement, air-voids and interfacial transition zone (ITZ) around aggregates. Adoption of these complex structures and material properties in numerical simulation would lead us to better understanding and design of concrete. In this work, the mesoscale model of concrete has been prepared from X-ray computerized tomography (CT) image. These images are converted into computer model and numerically simulated using commercially available finite element software. The mesoscale models are simulated under the influence of compressive displacement. The effect of shape and distribution of aggregates, continuous and discrete ITZ thickness, voids, and variation of mortar strength has been investigated. The CT scan of concrete cube consists of series of two dimensional slices. Total 49 slices are obtained from a cube of 150mm and the interval of slices comes approximately 3mm. In CT scan images, the same cube can be CT scanned in a non-destructive manner and later the compression test can be carried out in a universal testing machine (UTM) for finding its strength. The image processing and extraction of mortar and aggregates from CT scan slices are performed by programming in Python. The digital colour image consists of red, green and blue (RGB) pixels. The conversion of RGB image to black and white image (BW) is carried out, and identification of mesoscale constituents is made by putting value between 0-255. The pixel matrix is created for modeling of mortar, aggregates, and ITZ. Pixels are normalized to 0-9 scale considering the relative strength. Here, zero is assigned to voids, 4-6 for mortar and 7-9 for aggregates. The value between 1-3 identifies boundary between aggregates and mortar. In the next step, triangular and quadrilateral elements for plane stress and plane strain models are generated depending on option given. Properties of materials, boundary conditions, and analysis scheme are specified in this module. The responses like displacement, stresses, and damages are evaluated by ABAQUS importing the input file. This simulation evaluates compressive strengths of 49 slices of the cube. The model is meshed with more than sixty thousand elements. The effect of shape and distribution of aggregates, inclusion of voids and variation of thickness of ITZ layer with relation to load carrying capacity, stress-strain response and strain localizations of concrete have been studied. The plane strain condition carried more load than plane stress condition due to confinement. The CT scan technique can be used to get slices from concrete cores taken from the actual structure, and the digital image processing can be used for finding the shape and contents of aggregates in concrete. This may be further compared with test results of concrete cores and can be used as an important tool for strength evaluation of concrete.

Keywords: concrete, image processing, plane strain, interfacial transition zone

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Authors: Proud Arunrangsiwed

Abstract:

This study analyzes the crisis management and image repair strategies during the crisis of Mahidol Wittayanusorn School (MWIT) library burning. The library of this school was burned by a 16-year-old-male student on June 6th, 2010. This student blamed the school that the lesson was difficult, and other students were selfish. Although no one was in the building during the fire, it had caused damage to the building, books and electronic supplies around 130 million bahts (4.4 million USD). This event aroused many discourses arguing about the education system and morality. The strategies which were used during crisis were denial, shift the blame, bolstering, minimization, and uncertainty reduction. The results of using these strategies appeared after the crisis. That was the numbers of new students, who registered for the examination to get into this school in the later years, have remained the same.

Keywords: school, crisis management, violence, image repair strategies, uncertainty, burn

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Authors: Aniket S. Joshi, Aditya R. Mane, Arjun Tukaram

Abstract:

In the 21st century, in the era of e-world, people are continuously getting updated by daily information such as weather conditions, news, stock exchange market updates, new projects, cricket updates, sports and other such applications. In the busy situation, they want this information on the little use of keyboard, time. Today in order to get such information user have to repeat same mouse and keyboard actions which includes time and inconvenience. In India due to rural background many people are not much familiar about the use of computer and internet also. Also in small clinics, small offices, and hotels and in the airport there should be a system which retrieves daily information with the minimum use of keyboard and mouse actions. We plan to design application based project that can easily retrieve information with minimum use of keyboard and mouse actions and make our task more convenient and easier. This can be possible with an image processing application which takes real time hand gestures which will get matched by system and retrieve information. Once selected the functions with hand gestures, the system will report action information to user. In this project we use real time hand gesture movements to select required option which is stored on the screen in the form of RSS Feeds. Gesture will select the required option and the information will be popped and we got the information. A real time hand gesture makes the application handier and easier to use.

Keywords: hand detection, hand tracking, hand gesture recognition, HSV color model, Blob detection

Procedia PDF Downloads 283

Authors: Emily Fortune Super, Ameerah Khadaroo, Aurore Bardey

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Fashion models are often assumed to have a glamorous job with limited consideration for their well-being. This study aims to assess the well-being of models through semi-structured interviews with six professional fashion models and six industry professionals. Thematic analysis revealed that although models experienced improved self-confidence, they also reported heightened anxiety levels, body image issues, and the negative influence of modelling on their self-esteem. By contrast, industry professionals reported no or minimum concerns about anxious behaviours or the general well-being of fashion models. Being resilient as a model was perceived as an essential attribute to have by both models and industry professionals as they face recurrent rejection in this industry. These results demonstrate a significant gap in the current understanding of the well-being of fashion models between industry professionals and the models themselves. Findings imply that there is an inherent need for change in the modelling industry to promote and enhance their well-being.

Keywords: body image, fashion industry, modelling, well-being

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

Abstract:

China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.

Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron

Procedia PDF Downloads 386

Authors: Paramvir Singh

Abstract:

The locomotion of aquatic organisms has long fascinated biologists and engineers alike, with fish fins serving as a prime example of nature's remarkable adaptations for efficient underwater propulsion. This paper presents a comprehensive study focused on the hydrodynamic analysis of fish fin kinematics, employing an innovative approach that combines machine learning and image processing techniques. Through high-speed videography and advanced computational tools, we gain insights into the complex and dynamic motion of the fins of a Tilapia (Oreochromis Niloticus) fish. This study was initially done by experimentally capturing videos of the various motions of a Tilapia in a custom-made setup. Using deep learning and image processing on the videos, the motion of the Caudal and Pectoral fin was extracted. This motion included the fin configuration (i.e., the angle of deviation from the mean position) with respect to time. Numerical investigations for the flapping fins are then performed using a Computational Fluid Dynamics (CFD) solver. 3D models of the fins were created, mimicking the real-life geometry of the fins. Thrust Characteristics of separate fins (i.e., Caudal and Pectoral separately) and when the fins are together were studied. The relationship and the phase between caudal and pectoral fin motion were also discussed. The key objectives include mathematical modeling of the motion of a flapping fin at different naturally occurring frequencies and amplitudes. The interactions between both fins (caudal and pectoral) were also an area of keen interest. This work aims to improve on research that has been done in the past on similar topics. Also, these results can help in the better and more efficient design of the propulsion systems for biomimetic underwater vehicles that are used to study aquatic ecosystems, explore uncharted or challenging underwater regions, do ocean bed modeling, etc.

Keywords: biomimetics, fish fin kinematics, image processing, fish tracking, underwater vehicles

Procedia PDF Downloads 85

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

Procedia PDF Downloads 490