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All Journal Jurnal Ilmiah Poli Rekayasa JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Ilmiah Matrik JITSI : Jurnal Ilmiah Teknologi Sistem Informasi
Gusman, Taufik
Politeknik Negeri Padang
Computer Science & IT Education Engineering

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Journal : JOIV : International Journal on Informatics Visualization

 1 
Classifying Vehicle Types from Video Streams for Traffic Flow Analysis Systems Imran B. Mu’azam; Nor Fatihah Ismail; Salama A. Mostafa; Zirawani Baharum; Taufik Gusman; Dewi Nasien
JOIV : International Journal on Informatics Visualization Vol 6, No 1 (2022)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1.739

Abstract

This paper proposes a vehicle types classification modelfrom video streams for improving Traffic Flow Analysis (TFA) systems. A Video Content-based Vehicles Classification (VC-VC) model is used to support optimization for traffic signal control via online identification of vehicle types.The VC-VC model extends several methods to extract TFA parameters, including the background image processing, object detection, size of the object measurement, attention to the area of interest, objects clash or overlap handling, and tracking objects. The VC-VC model undergoes the main processing phases: preprocessing, segmentation, classification, and tracks. The main video and image processing methods are the Gaussian function, active contour, bilateral filter, and Kalman filter. The model is evaluated based on a comparison between the actual classification by the model and ground truth. Four formulas are applied in this project to evaluate the VC-VC model’s performance: error, average error, accuracy, and precision. The valid classification is counted to show the overall results. The VC-VC model detects and classifies vehicles accurately. For three tested videos, it achieves a high classification accuracy of 85.94% on average. The precession for the classification of the three tested videos is 92.87%. The results show that video 1 and video 3 have the most accurate vehicle classification results compared to video 2. It is because video 2 has more difficult camera positioning and recording angle and more challenging scenarios than the other two. The results show that it is difficult to classify vehicles based on objects size measures. The object's size is adjustable based on the camera altitude and zoom setting. This adjustment is affecting the accuracy of vehicles classification.
Virtual Campus Tour Application through Markerless Augmented Reality Approach Ang Wei Liang; Noorhaniza Wahid; Taufik Gusman
JOIV : International Journal on Informatics Visualization Vol 5, No 4 (2021)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.5.4.743

Abstract

Augmented Reality (AR) technology has been widely used on campus tours by universities all around the world. However, the students that stay very far away do not have a chance to visit around the campus. Also, the information that is available on the official website is static, resulting in the visitors feeling less engaged with the information. Hence, the virtual campus tour application using the markerless AR technology, namely AR-UTHM Tour is proposed to be developed on the Android mobile-based platform to visualize the buildings and facilities that are available in the university, specifically Universiti Tun Hussein Onn Malaysia (UTHM). This approach allows the users to visualize the 3D models by pointing the camera at any flat surface. Then, the feature point will be generated to generate a virtual plane. The information about the facilities was obtained from the UTHM official website and the 3D models of the buildings were referred to the floor plan and the actual images. The user acceptance test has been conducted on 30 students of UTHM using Technology Acceptance Model (TAM). The result shows that more than 50% of the respondents have successfully executed the AR session without any error. Overall results show that the users are satisfied with the AR-UTHM Tour application. In conclusion, this application is suitable to be used as a medium to introduce and promote UTHM virtually. Future improvements in terms of detailing the aesthetic of the 3D model will be taken into consideration.
Using Augmented Reality Application to Reduce Time Completion and Error Rate in PC Assembly Safiani Osman; Danakorn Nincarean Eh Phon; Nurul Aswa Omar; Mohd Rustam Mohd Rameli; Najua Syuhada Ahmad Alhassora; Taufik Gusman
JOIV : International Journal on Informatics Visualization Vol 4, No 3 (2020)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.4.3.245

Abstract

In the present context of globalization, the demand for assembly skill has increased and play an essential role in today’s industry. The traditional assembly instruction, face-to-face and manual instruction, may contain unimportant information that can result in misinterpretation, which in turn may increase the number of error and takes longer time to complete the task. A new technology (AR) claims to increase the efficiency of assembly task by directly visualizing computer generated 3D information in the real environment. Therefore, this study aims to determine the impact of AR on the time of task completion and the number of error made during the assembly task. The comparative user study was quantitative involving 18 users divided into either AR group or traditional group performing a pc assembly task. Statistical analysis revealed that the time of completion and error rate for two different group is statistically significant. The findings showed that the use of AR application has resulted in decreasing the number of error made and shorten the time to complete the task than the traditional instructional manual in assemble a pc. Considering these result, it can conclude that augmented reality application is an effective and beneficial tool to be applied in assembly and education.
Study the Field of View Influence on the Monchromatic and Polychromatic Image Quality of a Human Eye Adeeb Mansoor Qasim; Mohammad Aljanabi; Shahreen Kasim; Mohd Arfian Ismail; Taufik Gusman
JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.1-2.931

Abstract

In this paper, the effect of the eye field of view (known as F.O.V.) on the performance and quality of the image of the human eye is studied, analyzed, and presented in detail. The image quality of the retinal is numerically analyzed using the eye model of Liou and Brennan with this polymer contact lens. The image, which is in digital form were collected from various sources such as from photos, text structure, manuscripts, and graphics. These images were obtained from scanned documents or from a scene. The color fringing which is chromatic aberration addition to polychromatic effect was studied and analyzed. The Point Spreads Function or (known as PSF) as well as The Modulation Transfers Function (known as MTF) were measured as the most appropriate measure of image quality. The calculations of the image quality were made by using Zemax software. Then, the result of the calculation demonstrates the value of correcting the chromatic aberration. The results presented in this paper had shown that the form of image is so precise to the eye (F.O.V.). The image quality is degraded as (F.O.V.) increase due to the increment in spherical aberration and distortion aberration respectively. In conclusion, then Zemax software that was used in this study assist the researcher potential to design human eye and correct the aberration by using external optics.
Intervention Strategies through Interactive Gamification E-Learning Web-Based Application to Increase Computing Course Achievement Noor Zuraidin Mohd Safar; Hazalila Kamaludin; Masitah Ahmad; Muhammad Hanif Jofri; Norfaradilla Wahid; Taufik Gusman
JOIV : International Journal on Informatics Visualization Vol 6, No 2 (2022)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.2.1001

Abstract

This study aims to help students improve their knowledge capability based on their active participation through gamification. Gamification is one of the newer methods of education that has the potential to improve student learning. This research looked into gamification's efficacy in student engagement and learning retention during teaching and learning sessions for computer science or information technology courses. The assessment involved in this study is through Pre-Test and Post-Test through instructional intervention by adapting interactive Quizizz gamification e-learning web-based application. The flow of research works begins with a survey of the problem, pre-intervention analysis, and action was taken during the intervention, ending with the implementation and observation phase. The pre and post-analysis of test results and questionnaires were accomplished and discussed. Fifty-six respondents participate in this study. Results show that 87% of the respondents have increased their percentage of marks. In the pre-test result, 56% of the respondents achieved below the 55 marks, while in the post-test, it reduced to 14%. Adoption of other gamification applications, a larger target demographic, and the addition of computer science or information technology courses will help improve the study in the future.
Vehicles Speed Estimation Model from Video Streams for Automatic Traffic Flow Analysis Systems Maizatul Najihah Arriffin; Salama A. Mostafa; Umar Farooq Khattak; Mustafa Musa Jaber; Zirawani Baharum; - Defni; Taufik Gusman
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1820

Abstract

Image and video processing have been widely used to provide traffic parameters, which will be used to improve certain areas of traffic operations. This research aims to develop a model for estimating vehicle speed from video streams to support traffic flow analysis (TFA) systems. Subsequently, this paper proposes a vehicle speed estimation model with three main stages of achieving speed estimation: (1) pre-processing, (2) segmentation, and (3) speed detection. The model uses a bilateral filter in the pre-processing strategy to provide free-shadow image quality and sharpen the image. Gaussian filter and active contour are used to detect and track objects of interest in the image. The Pinhole model is used to assess the real distance of the item within the image sequence for speed estimation. Kalman filter and optical flow are used to flatten vehicle speed and acceleration uncertainties. This model is evaluated with a dataset that consists of video recordings of moving vehicles at traffic light junctions on the urban roadway. The average percentage for speed estimation error is 20.86%. The average percentage for accuracy obtained is 79.14%, and the overall average precision of 0.08.
Co-Authors Adeeb Mansoor Qasim Ang Wei Liang Danakorn Nincarean Eh Phon Dewi Nasien Fhadel Wedi Pratama Fitri Nova Nova Hazalila Kamaludin Hidra Amnur Imran B. Mu’azam Maizatul Najihah Arriffin Masitah Ahmad Meri Azmi Mohammad Aljanabi Mohd Arfian Ismail Mohd Rustam Mohd Rameli Muhammad Hanif Jofri Muhammad Umar Huzein Muhammad Yosazikri Ikhsan Mustafa Musa Jaber Najua Syuhada Ahmad Alhassora Noor Zuraidin Mohd Safar Noorhaniza Wahid Nor Fatihah Ismail Norfaradilla Wahid Nurul Aswa Omar Rasyidah, - Safiani Osman Salama A. Mostafa Salama A. Mostafa Sean Rayhan Shahreen Kasim Suci Ramadhani Tri Lestari Umar Farooq Khattak Yance Sonatha Zirawani Baharum Zirawani Baharum