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Articles by Norwati Mustapha
Total Records ( 5 ) for Norwati Mustapha
  Fereshteh Falah Chamasemani , Lilly Suriani Affendey , Norwati Mustapha and Fatimah Khalid
  Automatic video annotation has received a great deal of attention from researchers working on video retrieval. This study presents a novel automatic video annotation framework to enhance the annotation accuracy and reduce the processing time in large-scale video data by utilizing semantic concepts. The proposed framework consists of three main modules i.e., pre-processing, video analysis and annotation module. The framework support an efficient search and retrieval for any video content analysis and video archive applications. The experimental results on widely used TRECVID dataset using concepts of Columbia374 demonstrate the effectiveness of the proposed framework in assigning appropriate and semantically representative annotations for any new video.
  Tareef K. Mustafa , Norwati Mustapha , Masrah Azrifah Azmi and Nasir B. Sulaiman
  Problem statement: Stylometric authorship attribution is an approach concerned about analyzing texts in text mining, e.g., novels and plays that famous authors wrote, trying to measure the authors style, by choosing some attributes that shows the author style of writing, assuming that these writers have a special way of writing that no other writer has; thus, authorship attribution is the task of identifying the author of a given text. In this study, we propose an authorship attribution algorithm, improving the accuracy of Stylometric features of different professionals so it can be discriminated nearly as well as fingerprints of different persons using authorship attributes. Approach: The main target in this study is to build an algorithm supports a decision making systems enables users to predict and choose the right author for a specific anonymous author’s novel under consideration, by using a learning procedure to teach the system the Stylometric map of the author and behave as an expert opinion. The Stylometric Authorship Attribution (AA) usually depends on the frequent word as the best attribute that could be used, many studies strived for other beneficiary attributes, still the frequent word is ahead of other attributes that gives better results in the researches and experiments and still the best parameter and technique that’s been used till now is the counting of the bag-of-word with the maximum item set. Results: To improve the techniques of the AA, we need to use new pack of attributes with a new measurement tool, the first pack of attributes we are using in this study is the (frequent pair) which means a pair of words that always appear together, this attribute clearly is not a new one, but it wasn’t a successive attribute compared with the frequent word, using the maximum item set counters. the words pair made some mistakes as we see in the experiment results, improving the winnow algorithm by combining it with the computational approach, achieved by using the CV statistical tool as a conditional threshold for attribute selecting; by doing so, the frequent pair result improved from 50% error to 0% in the improved frequent pair with a clear higher score result compared with the frequent word attribute. Conclusion/Recommendations: The new CV algorithm results improvement may lead to several new attributes usage that gave unsatisfying results before that might improve the direction for solving some hard cases couldn’t be solved till now.
  Hassan H. Khalil , Rahmita O.K. Rahmat , D.M. Zamrin , Ramlan Mahmod and Norwati Mustapha
  Problem statement: Whereas most of the conventional techniques propose using multi-view cineangiograms to reconstruct 3D objects this article proposes to integrate a Three Dimension (3D) model of the coronary artery tree using a standard single-view cineangiogram. Splitting the cineangiograms into non-sequenced and different angle views is how the data is supplied in this method. Each single view can be used to reconstruct a robust 3D model of the coronary artery from that angle of view. Although the dynamic variations of blood vessels curvature have been difficult to study in Two Dimension (2D) angiograms, there is both experimental and clinical evidence showing that 3D coronary reconstruction is very useful for surgery planning and clinical study. Approach: The algorithm has three stages. The first stage is the vessel extraction and labeling for each view for the purpose of constructing the 3D model, while in the second stage, the vessels information (x, y and z) will be saved in a data file to be forwarded to the next stage. Finally, we input the x, y and z of a specific coronary artery tree to the OPENGL library included in the software, which we developed and called Fast 3D (F3D) and which is displayed in R3. Results: Experimental evaluation has been done to clinical raw data sets where the experimental results revealed that the proposed algorithm has a robust 3D output. Conclusion: Results showed that our proposed algorithm has high robustness for a variety of image resolutions and voxel anisotropy.
  Hassan H. Khalil , Rahmita O.K. Rahmat , D.M. Zamrin , Ramlan Mahmod and Norwati Mustapha
  Problem statement: Three-Dimension (3D) reconstruction is one of the vital and robust tools that provide aid in many fields, especially medicine. This article is about 3D shape similarity and it presents a comparison approach between principal curvature methods of 3D output. Our approach follows the concept of using the gray scale value as the z dimension and the other approach is a standard one. A comparison of the curvature of the 3D outputs will be made between the standard approach and our proposed one to prove its correctness. We propose to use the standard deviation technique to compare the output features of the 3D coronary artery trees. We applied a standard approach of 3D shape similarity and compared the features with ours. The standard approach was published in 1998 as a study comparing certain 3D curvature measurement algorithms. Approach: Our approach consists of three major steps: (1) Apply the paraboloid fitting technique from the standard approach; (2) Apply the 3D reconstruction algorithm proposed in this research on the same data in step (1) and (3) Apply the Standard Deviation technique on both outputs from (1) and (2) and compare the outputs. Results: Experimental evaluation has been done on clinical raw data sets where the experimental results revealed that both outputs are totally matched. Conclusion: The match in the output refers to the correctness of the proposed 3D output and subsequently its coronary artery tree curvature as well.
  Abdul Rafiez Abdul Raziff , Nasir Sulaiman , Norwati Mustapha and Thinagaran Perumal
  Gait identification has been a well-known type of biometric recognition for many purposes. However, the usage and its application are still limited due to uncertainty factors that lead to its lack of use. One of the factors is the position of the smartphone. Current research uses pouch, pocket and other parts of the body but not handheld. The second factor is the nonstationary data that resemble the person which contains only a few meaningful dataset for learning purposes. The third factor is the ability of the classifier itself whether is it efficient enough in tackling the multiclass problem. In this research, investigation on the handheld smartphone position is proposed. Besides that SMOTE is applied to the dataset to increase its sample data before the training procedure. For classification, OVO multiclass structure is proposed instead of using a single classifier algorithm. From the result, it shows that handheld placement of the smartphone is viable for gait recognition. At the same time, using SMOTE and OVO methods do increase the accuracy of the gait identification.
 
 
 
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