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Articles by Md. Jan Nordin
Total Records ( 6 ) for Md. Jan Nordin
  Ghassan Jasim AL-Anizy , Md. Jan Nordin and Mohammed M. Razooq
  Driver drowsiness is the most critical cause of traffic accidents, thus drowsiness detection play a vital role in preventing traffic accidents. By developing an automatic solution for alerting drivers of drowsing, before an accident occurs, this could reduce the number of traffic accidents. Therefore, this research proposes a real-time detection approach for driver drowsiness. The proposed approach has two phases: image processing and machine learning. The role of image processing phase is to recognize the face of the driver and then extracts the image of the eyes of the driver. This phase uses Haar face detection algorithm that takes captured frames of image as input and then the detected face as output. Next, Haar is also used to extract the eyes image from the detected face which will be used as an input for the machine learning phase. The main role of the machine learning is to classify either the eyes of the driver are closed or opened using Support Vector Machine (SVM). If the result of the classification indicates that the driver’s eyes is closed for a predefined period of time, the eyes of the driver will be considered closed and hence an alarm will be started to alert the driver. The proposed methodology has been tested on available benchmark data. The result demonstrates the accuracy and robustness of the hybridized of image processing technique with machine learning technique. Thus, it can be concluded that the proposed approach is an effective solution method for a real-time of driver drowsiness detection.
  Iman Mohammed Burhan and Md. Jan Nordin
  Gait is an overall perceived biometric gimmick that is utilized to distinguish a human at a separation. Gait Recognition (GR) systems encounter several challenges, including viewing angles and translation variations. Hence, GR systems require the development of a robust gait representation model which is invariant in varying conditions. As such, this study presents a gait representation model for Multi-view Gait Recognition Systems (MvGRS) based on Gait Energy Image (GEI) and Radon Transform (RT) on human silhouettes to overcome the challenges in human recognition. In this regard, GEI is utilized for the description of gait features of binary silhouette images which are robust in multi-viewing and varied in appearances. Furthermore, the adoption of Radon Transform (RT) allows for the accommodation of gait representation model with RT features and silhouette alignment. This is to overcome the difficulties in geometrical transformation such as translation, scale and rotation. Consequently robust Principal Component Analysis (PCA) and Partial Least Square (PLS) approaches are accomplished in the reduction of these dimension feature vectors and feature selection. Finally, the recognition of gaits is based on similarity in measurements using Euclidean distance. The experiments were conducted on the public data set of CASIA. The findings from these experiments show that the results are better in comparison with the other methods. Thus, this indicates that the proposed method for gait recognition can outperform the existing methods in gait recognition.
  M. Khamiss , S. Algabary , Khairuddin Omar , Md. Jan Nordin and Siti Norul Huda S. Abdullah
  This study presents a brief processing of ear identification and making an improvement of ear recognition via combination of Iterative Closest Point (ICP) algorithm with the Stochastic Clustering Method (SCM). The objective of this study is to enhance the matching template scheme using BPNN based on the ICP algorithm combined SCM method. An effective SLLE (Supervised Locality Linear Embedding) variation for ear recognition was designed based on JAVA programming language. The software provides basic functions for ear identification analysis by using two kinds of algorithm, respectively. In particular, the combined method provides effective identification through BPNN environment condition. Analysis results are expressed realistically through different database. Finally, with the application of ICP and SCM based multilayer neutral network to identify 20 ear images, the experiment results shows 96.12% accuracy.
  Abbas M. Ali and Md. Jan Nordin
  Problem statement: Navigation for visually impaired people needs to exploit more approaches for solving problems it has, especially in image based methods navigation. Approach: This study introduces a new approach of an electronic cane for navigation through the environment. By forming multi clouds of SIFT features for the scene objects in the environment using some considerations. Results: The system gives an efficient localization within the weighted topological graph. Instead of building a metric (3D) model of the environment, it helps the blind person to navigate more confidently. The work efforts towards conceptualizing environment on the basis of the human compatible representation so formed. Such representation and the resulting conceptualization would be useful for enabling blind persons to be cognizant of their surroundings. The identification of different scenes to the blind person has done by clouds of three or two objects. These clouds grouped the stored objects into meaningful groups used in localization of a cane with single web camera as an external sensor. Conclusion: The approach is useful to divide the space environment into meaning partitions and helps to detect sites and objects needed from the blind person in very sufficient way with in the map.
  Abdulsamad Ebrahim Yahya and Md. Jan Nordin
  Problem statement: Iris segmentation is one of the most important steps in iris recognition system and determines the accuracy of matching. Most segmentation methods in the literature assumed that the inner and outer boundaries of the iris were circular. Hence, they focus on determining model parameters that best fit these hypotheses. This is a source of error, since the iris boundaries were not exactly circles. Approach: In this study we proposed an accurate iris segmentation method that employs Chan-Vese active contour method to extract the iris from his surrounding structures. Results: The proposed method was implemented and tested on the challenging UBIRIS database the results indicated the efficacy of the proposed method. Conclusion: The experimental results showed that the proposed method localized the iris area probably even when the eyelids occlude same part of iris.
  Awang Hendrianto Pratomo , Anton Satria Prabuwono , Mohd. Shanudin Zakaria , Khairuddin Omar , Md. Jan Nordin , Shahnorbanun Sahran , Siti Norul Huda Sheikh Abdullah and Anton Heryanto
  Problem statement: Robot soccer is an attractive domain for researchers and students working in the field of autonomous robots. However developing (coding, testing and debugging) robots for such domain is a rather complex task. Approach: This study concentrated on developing position and obstacle avoidance algorithm in robot soccer. This part is responsible for realizing soccer skills such as movement, shoot and goal keeping. The formulation of position and obstacle avoidance was based on mathematical approach. This formula is to make sure that the movement of the robot is valid. Velocity of the robot was calculated to set the speed of the robot. The positioning theory including the coordination of the robot (x,y) was used to find the obstacle and avoid it. Results: Some simulations and testing had been carried out to evaluate the usefulness of the proposed algorithms. The functions for shooting, movement and obstacle avoidance had been successfully implemented. Conclusion: The results showed its possibility could be used as strategy algorithms in real robot soccer competition.
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