2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)最新文献_第3页

Lung Area Segmentation on Chest X-Ray Based on Texture Image Feature 基于纹理图像特征的胸部x射线肺区域分割

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530963

M. Saad, M. Mohsin, H. Hamid, Z. Muda

{"title":"Lung Area Segmentation on Chest X-Ray Based on Texture Image Feature","authors":"M. Saad, M. Mohsin, H. Hamid, Z. Muda","doi":"10.1109/ICCSCE52189.2021.9530963","DOIUrl":"https://doi.org/10.1109/ICCSCE52189.2021.9530963","url":null,"abstract":"Advanced technology has permitted many innovations in computer aided diagnostics. One of the most popular studies done to the medical image is to segment specific body areas such as the lung for further image analysis. The segmentation of lung area in chest X-ray (CXR) based regular techniques such as contour and level set based are popular however these methods are timely and require special initialization process or else it will accidently cause false positive area selection. Therefore, the requirement for a better segmentation method to segment the lung area in CXR image should be highlighted. A quick solution to cope with this obstacle is to propose a noble feature extraction technique based on texture feature using the Gray Level Co-Occurrence Matrix (GLCM) so that image features could be grouped together based on similar feature vectors. Therefore, in this paper we are sharing our experience conducting a lung segmentation experiment using the CXR image. In order to execute the experiment we also shared six processes that are the common method in the lung segmentation task. The segmentation output derived from the experiment shows a promising appearance although it is not accurately similar with the original lung area in the actual image.","PeriodicalId":285507,"journal":{"name":"2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122650431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Design and Implementation of Needle Steering System 针转向系统的设计与实现

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530973

Abdel-Salam Shaaban, Ahmed S. Ali, R. Mostafa, F. El-Samie

引用次数: 0

Performance Evaluation of EHA System in the Presence of Mass and Pressure Variation using MOPSO-SMC 基于MOPSO-SMC的质量压力变化环境下EHA系统性能评价

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530918

C. M. Shern, R. Ghazali, Chong Shin Horng, C. C. Soon, Y. M. Sam, Zulfatman Has

{"title":"Performance Evaluation of EHA System in the Presence of Mass and Pressure Variation using MOPSO-SMC","authors":"C. M. Shern, R. Ghazali, Chong Shin Horng, C. C. Soon, Y. M. Sam, Zulfatman Has","doi":"10.1109/ICCSCE52189.2021.9530918","DOIUrl":"https://doi.org/10.1109/ICCSCE52189.2021.9530918","url":null,"abstract":"The usage of the Electro-Hydraulic Actuator (EHA) system in industrial machinery has increasingly attracted public attention nowadays by providing a highly stable output performance due to its incompressible hydraulic fluid. However, the accuracy and positioning control of the hydraulic cylinder are always become issues to engineers or researchers that utilized that actuator. In this paper, a suitable control strategy with a combination of a controller and optimization technique is proposed to control the EHA system. Three types of control strategies are proposed and studied in this paper which are PSO-PID, PSO-SMC, and MOPSO-SMC. This study is conducted through a simulation environment using MATLAB/Simulink with an established EHA system model. This paper focuses on three types of simulation studies which are tracking point analysis, mass variation simulation and pressure variation simulation. The overshoot percentage and steady-state error are used to evaluate and compare the effectiveness of the controller to the EHA system. The simulation results show that the EHA system controlled by MOPSO-SMC having the best output performance with the least overshoot percentage and steady-state error.","PeriodicalId":285507,"journal":{"name":"2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131221103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fall Detection System Using Wearable Sensors with Automated Notification 使用带有自动通知的可穿戴传感器的跌倒检测系统

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530983

A. H. M. Saod, Aisamuddin Aizat Mustafa, Z. H. C. Soh, S. A. Ramlan, N. A. Harron

引用次数: 1

PI Control of Biomass Concentration for a Continuous-Discrete Bioreactor 连续-离散生物反应器生物质浓度的PI控制

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530943

R. Ramjug-Ballgobin, K. Busawon, R. King, H. Rughooputh

引用次数: 0

Classification System for Leukemia Cell Images based on Hu Moment Invariants and Support Vector Machines 基于Hu矩不变性和支持向量机的白血病细胞图像分类系统

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530974

Y. Jusman, S. Riyadi, A. Faisal, S. N. A. Kanafiah, Z. Mohamed, R. Hassan

{"title":"Classification System for Leukemia Cell Images based on Hu Moment Invariants and Support Vector Machines","authors":"Y. Jusman, S. Riyadi, A. Faisal, S. N. A. Kanafiah, Z. Mohamed, R. Hassan","doi":"10.1109/ICCSCE52189.2021.9530974","DOIUrl":"https://doi.org/10.1109/ICCSCE52189.2021.9530974","url":null,"abstract":"Leukemia is cancer that attacks the tissues of white blood cells. It occurs when the body produces abnormal blood cells exceeding normal limits; thus, causing them not to function properly. It has a huge effect on the immune system of humans. Medical personnel currently need a long time to recognize leukemia and distinguish acute leukemia cells from normal cells. This study aims to build a classification system of white blood cell images using a feature extraction technique with Hu moment invariants and Support Vector Machine (SVM) classification methods. In this study, the data of 800 blood image samples were divided into two classes, acute and normal, with each class having 400 sample images. The calculation of the average accuracy and average time value on the system obtained the accuracy value of 88% and the required time of 3.73 seconds. The highest accuracy values for the testing data is 95% with duration time 0.89 seconds. The system could classify the leukemia images using Hu moment invariants and SVM.","PeriodicalId":285507,"journal":{"name":"2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128634930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

System Identification Makes Sense of Complex Measurements 系统识别使复杂测量变得有意义

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530875

M. Taib, N. Ismail

引用次数: 2

Control of Electric Wheelchair via Eye Gestures for People with Neurological Disorder 神经障碍患者用眼动手势控制电动轮椅

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530744

A. R. Adnan, S. Z. Yahaya, Z. Hussain

{"title":"Control of Electric Wheelchair via Eye Gestures for People with Neurological Disorder","authors":"A. R. Adnan, S. Z. Yahaya, Z. Hussain","doi":"10.1109/ICCSCE52189.2021.9530744","DOIUrl":"https://doi.org/10.1109/ICCSCE52189.2021.9530744","url":null,"abstract":"Tetraplegia is a total paralysis due to injury at C1 - C5 - T1 of spinal cord. People with tetraplegia have very limited or no muscle function from area below the neck. For mobility, electric wheelchair is a good option. However, since commercial electric wheelchair used joystick as its movement control, this is quite difficult for tetraplegic patients to use it. Facial features such as eyes gestures have the potential to be manipulated as instruction to control the movement of electric wheelchair. Therefore, this work aims to develop a system that can classify different eyes gestures of human subject and convert it into different state of control instructions. Methods for object detection that had been developed by researchers in recent years are suitable to be used to detect faces and eyes. This work proposed the combination use of Haar Cascade classifier and Dlib facial detector for detecting face and eye region, respectively. Next, several image enhancement techniques and morphological operations are performed to detect the iris. Image moments is used to calculate the center coordinate of the iris. Afterward, the iris coordinate is used to determine the classification of eye gestures. The proposed method has been proven to be efficient in detecting eyes gestures. The ratio of detection accuracy is ranged between 73.5% and 99.83% depending on the ambient lighting.","PeriodicalId":285507,"journal":{"name":"2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124049070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Content Based-Image Retrieval Using Support Vector Machine 基于内容的支持向量机图像检索

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530873

Syazwani Izzati Shahrom, Norlyda Mohamed, S. F. Kamarudin, Wan Ghazali, A. Malek

{"title":"Content Based-Image Retrieval Using Support Vector Machine","authors":"Syazwani Izzati Shahrom, Norlyda Mohamed, S. F. Kamarudin, Wan Ghazali, A. Malek","doi":"10.1109/ICCSCE52189.2021.9530873","DOIUrl":"https://doi.org/10.1109/ICCSCE52189.2021.9530873","url":null,"abstract":"Image retrieval is an important problem in multimedia systems. It is determined as the process of searching and fetching images from a dataset. Content-based Image Retrieval (CBIR) is a significant and challenging field of research in digital image processing. The CBIR system’s essential requirement is to retrieve the relevant information following a query image with higher system output from a large image database. Unfortunately, not all the methods are suitable to be used to get high accuracy of retrieval. Therefore, this research aims to classify the data of query image with the data of image database to get a similar image retrieval using Support Vector Machine (SVM) and validate its accuracy based on the classification for the performance evaluation using the precision-recall measure. The critical point of SVM is to get an optimal hyperplane that separates the data points into two classes. This method was applied to different image databases because the classified-based proposed scheme proved better performance than various existing methods. This project assessed experimental results toward 500 images of the Caltech-256 image dataset to demonstrate the proposed method. For retrieving a similar image following the query image, 20 images from five classes were successfully retrieved by using this method. It will show that the SVM method’s average accuracy from all image classes is 94.79%.","PeriodicalId":285507,"journal":{"name":"2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129730451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Human Body Temperature Detection based on Thermal Imaging and Screening using YOLO Person Detection 基于热成像和筛选的YOLO人体体温检测

2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2021-08-27 DOI: 10.1109/ICCSCE52189.2021.9530864

Muhammad Faizul Azwan Mushahar, N. Zaini

{"title":"Human Body Temperature Detection based on Thermal Imaging and Screening using YOLO Person Detection","authors":"Muhammad Faizul Azwan Mushahar, N. Zaini","doi":"10.1109/ICCSCE52189.2021.9530864","DOIUrl":"https://doi.org/10.1109/ICCSCE52189.2021.9530864","url":null,"abstract":"In addressing the worldwide Covid-19 outbreak, one of the actions to curb the spread of the virus is to keep people with Covid-19 symptoms away from others in public places. The most easily detected symptom is high body temperature due to fever, and this is one of the common symptoms of Covid-19 patients. Several methods of body temperature detection have been implemented at the entrance of the premises. One of the most common methods is to use an infrared temperature scanner. This method has some constraints including its use which is time-consuming and can lead to further spread of the virus as gun-type scanners can be a medium of virus spread as has been held by many people. Another more advanced method is the detection of body temperature through a thermal camera with imaging. Although more sophisticated, this method also has the constraint where the temperature is usually detected as a whole and does not differentiate the temperature of the human body and other nearby objects. With a focus on this problem, this study applies a combination of object detection methods through image processing with temperature detection through thermal imaging. For the object detection process, the You Only Look Once (YOLO) model and the OpenCV library have been used, especially in detecting people and non-people. While the calculation of body temperature through thermal images has been made more accurate because the scanned temperature is more specific based on the detected objects. In this way, a person’s body temperature can be separated and will not be affected by the temperature of other objects. From the results and analysis obtained, an accuracy of 100% can be achieved based on a pre-trained model for human body temperature detection. With more specific and accurate detection as produced in this study, then a warning or caution will be issued only when a person actually has a high body temperature and will then not be allowed to enter the premises.","PeriodicalId":285507,"journal":{"name":"2021 11th IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116224032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3