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Articles by Fatimah Khalid
Total Records ( 3 ) for Fatimah Khalid
  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.
  Seyed Hashem Davarpanah , Fatimah Khalid and Maryam Golchin
  Problem statement: To extract the moving objects, vision-based surveillance systems subtract the current image from a predefined background image. The efficiency of these systems mainly depends on accuracy of the extracted background image. It should be able to adapt to the changes continuously. In addition, especially in real-time applications the time complexity of this adaptation is a critical matter. Approach: In this study, to extract an adaptive background, a combination of blocking and multi-scale methods is presented. Because of being less sensitive to local movements, block-based techniques are proper to control the non-stationary objects’ movements, especially in outdoor applications. They can be useful to reduce the effect of these objects on the extracted background. We also used the blocking method to intelligently select the regions which the temporal filtering has to be applied on. In addition, an amended multi-scale algorithm is introduced. This algorithm is a hybrid algorithm, a combination of some nonparametric and parametric filters. It uses a nonparametric filter in the spatial domain to initiate two primary backgrounds. In continue two adapted two-dimensional filters will be used to extract the final background. Results: The qualitative and quantitative results of our experiments certify not only the quality of the final extracted background is acceptable, but also its time consumption is approximately half in compare to the similar methods. Conclusion: Using Multi scaling filtering and applying the filters just to some selected non-overlapped blocks reduce the time consumption of the extracting background algorithm.
  Eimad Eldin Abdu Abusham , Housam Khalifa Bashier , Fatimah Khalid , Shohel Sayeed , Jakir Hossen and S.M.A. Kalaiarasi
  The problem associated with Illumination variation is one of the major problems in image processing, pattern recognition, medical image, etc; hence there is a need to handle and deal with such variations. This paper presents a novel and efficient algorithm for images illumination normalization called Eimad-Housam Technique (EHT). EHT features are derived from a general definition of texture in a local graph neighborhood. The experiment results show the effectiveness of proposed algorithm.
 
 
 
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