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Fully Automated Attendance Record System Using Template Matching Technique

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Fully Automated Attendance Record System Using Template Matching Technique
International Journal of Engineering & Technology IJET-IJENS Vol: 10 No: 03

57

Fully Automated Attendance Record System using Template Matching Technique
Tabassam Nawaz†, Amber Assad††, Zunaira Khalil††† tabassam.nawaz@uettaxila.edu.pk , amberasad2003@yahoo.co.uk , zunaira0001@yahoo.com

of Software Engineering, University of Engineering & Technology Taxila, Pakistan of Software Engineering, University of Engineering & Technology Taxila, Pakistan ††† Department of Software Engineering, University of Engineering & Technology Taxila, Pakistan
†† Department

†Faculty

Summary This research paper “Fully Automated Attendance Record System using Template Matching Technique” focuses on the need to design a system that will automatically arrange the record and calculate the average attendance of each student. Manual attendance record system is not efficient and requires time to arrange record and to calculate the average attendance of each individual student. The Attendance Record System is intended to replace the manual model of attendance record keeping. The paper describes an efficient image processing algorithm that reads the scanned hard copy accurately and further calculates the absence or presence accordingly. In Image processing, noise is present in scanned images. This noise must be removed from scanned images. The Paper also describes a noise removal method that will remove noise efficiently from scanned images. Key words: Median Filter, Region based segmentation, template matching, pattern recognition, convolution

arrange the record and calculate the average attendance of each student. The proposed Attendance Record System is intended to replace the manual model. The system contains attendance records in electronic files containing details of absence or presence of a specific student enrolment during a semester. This project will try to organize the current university attendance record system that will be much quicker and will save time of



References: [1] Te-Won Lee And Michael S. Lewicki “Unsupervised Image Classification, Segmentation And Enhancement Using Ica Mixture Models” Ieee Transactions On Image Processing, Vol. 11, No. 3, March 2002 [2] Hua Li, Abderrahim Elmoataz Jaral Fadili Su Ruan “An Improved Image Segmentation Approach Based On Level Set And Mathematical Morphology” Third International Symposium On Multispectral Image Processing And Pattern Recognition [3] Ilya Pollak, Alan S. Willsky, Fellow, And Hamid Krim, Fellow,“Image Segmentation And Edge Enhancement With Stabilized Inverse Diffusion Equations” Ieee Transactions On Image Processing, Vol. 9, No. 2, February 2000 [5] Tabassam Nawaz, Khurram Ashfaq Qazi, M Imran Ashraf “Efficient Noise Removal Algorithm From A Torn Paper” 12th International Conference On Computer Graphics And Artificial Intelligence 3IA, 2009 Athens, Greece [6] Tabassam Nawaz, Khurram Ashfaq Qazi, M Imran Ashraf “Performance Evaluation of Noise Removal Algorithms for Scanned Images” 12th International Conference On Computer Graphics And Artificial Intelligence 3IA, 2009 Athens, Greece International Journal of Engineering & Technology IJET-IJENS Vol: 10 No: 03 64 [7] Gabriele Peters And Jochen Kerdels “Image Segmentation Based On Height Maps” Proceedings Of The 12th International Conference On Computer Analysis Of Images And Patterns, Vienna, Austria, August 27-29, 2007. [8] Mario A. Nascimento, Veena Sridhar, Xiaobo Li “Effective And Efficient Region-Based Image Retrieval” Journal Of Visual Languages And Computing [9] Lifeng Liu And Stan Sclaroff_ “Region Segmentation Via Deformable Model-Guided Split And Merge” Boston University Computer Science Technical Report No. 2000-24, Dec. 2000 [10] Sinisa Todorovic And Narendra Ahuja “Scale-Invariant Region-Based Hierarchical Image Matching”19th International Conference On Pattern Recognition (Icpr), Tampa, Fl, December 2008 [11] Lifeng Liu And Stan Sclaroff “Region Segmentation Via Deformable Model-Guided Split And Merge” Boston University Computer Science Technical Report No. 2000-24, Dec. 2000 [12] Fabiana Zama “Image Denoising And Segmentation Using Comsol Multiphysics” Excerpt From The Proceedings Of The Comsol Users Conference 2007 Grenoble [13] H C Sateesh Kumar 1, K B Raja2, Venugopal K R2 And L M Patnaik “Automatic Image Segmentation Using Wavelets” Ijcsns International Journal Of Computer Science And Network Security, Vol.9 No.2, February 2009 [14] Mario A. Nascimento*, Veena Sridhar, Xiaobo Li “Effective And Efficient Region-Based Image Retrieval” Journal Of Visual Languages And Computing 14 (2003) 151–179 [15]Hakan C¸ Aglar, Sinan Gu¨Ntu¨Rk, Bu¨Lent Sankur, And Emin Anarim “Vq-Adaptive Block Transform Coding Of Images” Ieee Transactions On Image Processing, Vol. 7, No. 1, January 1998

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